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train · 59.3k rows

repo_name stringlengths 6 77	path stringlengths 8 215	license stringclasses 15 values	cells list	types list
karlstroetmann/Formal-Languages	Python/FSM-2-Dot.ipynb	gpl-2.0	[ "from IPython.core.display import HTML\nwith open('../style.css', 'r') as file:\n css = file.read()\nHTML(css)", "The function dfa2string converts the given deterministic <span style=\"font-variant:small-caps;\">Fsm</span> into a string.", "def dfa2string(Fsm):\n states, sigma, delta, q0, final = Fsm\n ...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
rickiepark/tfk-notebooks	first-contact-with-tensorflow/chapter5_convolution_neural_network.ipynb	mit	[ "simple_neural_network 예제에서 MNIST 데이터를 이미 다운 받았으므로 다시 다운 받지 않습니다.", "from tensorflow.examples.tutorials.mnist import input_data\nmnist = input_data.read_data_sets('MNIST_data', one_hot=True)\nimport tensorflow as tf", "x, y_ 플레이스홀더를 지정하고 x 를 28x28x1 크기로 차원을 변경합니다.", "x = tf.placeholder(\"float\", shape=[None,...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
tritemio/FRETBursts	notebooks/Example - Customize the us-ALEX histogram.ipynb	gpl-2.0	[ "Example - Customize the μs-ALEX histogram\nThis notebook is part of smFRET burst analysis software FRETBursts.\n\nIn this notebook shows how to plot different styles of μs-ALEX histograms and $E$ and $S$ marginal distributions.\nFor a complete tutorial on burst analysis see \nFRETBursts - us-ALEX smFRET burst anal...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
StingraySoftware/notebooks	Simulator/Concepts/Inverse Transform Sampling.ipynb	mit	[ "Inverse Transform Sampling\nThis notebook will conceptualize how inverse transform sampling works", "import numpy as np\nfrom matplotlib import pyplot as plt\nimport numpy.random as ra\n\n%matplotlib inline", "Below is a spectrum which follows an almost bell-curve type distribution (anyway, the specific type o...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
spacedrabbit/PythonBootcamp	Advanced Python Objects - Test.ipynb	mit	[ "Advanced Python Objects Test\nAdvanced Numbers\nProblem 1: Convert 1024 to binary and hexadecimal representation:", "print bin(1024)\nprint hex(1024)", "Problem 2: Round 5.23222 to two decimal places", "print round(5.2322, 2)", "Advanced Strings\nProblem 3: Check if every letter in the string s is lower ca...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
diegocavalca/Studies	programming/Python/tensorflow/exercises/Seq2Seq_solutions.ipynb	cc0-1.0	[ "from __future__ import print_function\nimport numpy as np\nimport tensorflow as tf\nimport matplotlib.pyplot as plt\n%matplotlib inline\n\ntf.__version__\n\nnp.__version__\n\nauthor = \"kyubyong. https://github.com/Kyubyong/tensorflow-exercises\"\n\nnp.random.seed(0)", "Q1. Let's practice the seq2seq framework w...	[ "code", "markdown", "code", "markdown", "code" ]
Cyb3rWard0g/HELK	docker/helk-jupyter/notebooks/tutorials/04-Intro_pyspark_sparkSQL.ipynb	gpl-3.0	[ "Introduction to Spark SQL via PySpark\n\nGoals:\n\nGet familiarized with the basics of Spark SQL and PySpark\nLearn to create a SparkSession\nVerify if Jupyter can talk to Spark Master\n\nReferences:\n* https://spark.apache.org/docs/latest/api/python/pyspark.html\n* https://spark.apache.org/docs/latest/sql-getting...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
opengeostat/pygslib	pygslib/Ipython_templates/broken/vtk_tools.ipynb	mit	[ "VTK tools\nPygslib use VTK:\n\nas data format and data converting tool\nto plot in 3D\nas a library with some basic computational geometry functions, for example to know if a point is inside a surface\n\nSome of the functions in VTK were obtained or modified from Adamos Kyriakou at https://pyscience.wordpress.com/...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
bmanubay/open-forcefield-tools	examples/substructure_linking.ipynb	mit	[ "Linking molecule fragments via reaction SMIRKS\nTo test/develop SMIRFF force fields, it is extremely helpful to be able to generate molecules containing assorted combinations of various molecular fragments or substructures (i.e. substructures containing particular SMIRKS). Here, I experiment with using reaction SM...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
kubeflow/kfp-tekton	samples/katib/early-stopping.ipynb	apache-2.0	[ "Kubeflow Pipelines with Katib component\nIn this notebook you will:\n- Create Katib Experiment using random algorithm.\n- Use median stopping rule as an early stopping algorithm.\n- Use Kubernetes Job with mxnet mnist training container as a Trial template.\n- Create Pipeline to get the optimal hyperparameters.\nR...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
fionapigott/Data-Science-45min-Intros	python-decorators-101/python-decorators-101.ipynb	unlicense	[ "Python decorators\nJosh Montague, 2015-12\nBuilt on OS X, with IPython 3.0 on Python 2.7\nIn this session, we'll dig into some details of Python functions. The end goal will be to understand how and why you might want to create decorators with Python functions.\n\nNote: there is an Appendix at the end of this note...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
dianafprieto/SS_2017	.ipynb_checkpoints/05_NB_VTKPython_Scalar-checkpoint.ipynb	mit	[ "<img src=\"imgs/header.png\">\nVisualization techniques for scalar fields in VTK + Python\nReminder: The VTK pipeline\n<img src=\"imgs/vtk_pipeline.png\", align=left>\n$~$\nVisualizing data within a recilinear grid\nThe following code snippets show step by step the how to create a pipeline to visualize the outline...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
smsaladi/murraylab_tools	examples/Echo Setup Usage Examples.ipynb	mit	[ "Welcome to the Echo package\nThe \"echo\" subpackage of murraylab_tools is designed to automate the setup of reactions (mostly TX-TL reactions) with the Echo. The EchoRun class can produce picklists for the Echo, as well as instructions for loading a source plate to go with those instructions, when appropriate. \n...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
ES-DOC/esdoc-jupyterhub	notebooks/mpi-m/cmip6/models/mpi-esm-1-2-lr/seaice.ipynb	gpl-3.0	[ "ES-DOC CMIP6 Model Properties - Seaice\nMIP Era: CMIP6\nInstitute: MPI-M\nSource ID: MPI-ESM-1-2-LR\nTopic: Seaice\nSub-Topics: Dynamics, Thermodynamics, Radiative Processes. \nProperties: 80 (63 required)\nModel descriptions: Model description details\nInitialized From: -- \nNotebook Help: Goto notebook help pag...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
Upward-Spiral-Science/spect-team	Code/Assignment-10/SubjectSelectionExperiments (rCBF data).ipynb	apache-2.0	[ "Subject Selection Experiments disorder data - Srinivas (handle: thewickedaxe)\nInitial Data Cleaning", "# Standard\nimport pandas as pd\nimport numpy as np\n%matplotlib inline\nimport matplotlib.pyplot as plt\n\n# Dimensionality reduction and Clustering\nfrom sklearn.decomposition import PCA\nfrom sklearn.cluste...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
cosmoscalibur/herramientas_computacionales	Presentaciones/Notas/09_Extraccion_web.ipynb	mit	[ "Extracción de datos web (Web scrapping)\nAnte la generación masiva a traves de la red es importante tener herramientas que permitan la extracción de datos a partir de fuentes cuya ubicación es esta. De esto se trata el web scrapping. \nSe pueden tener elementos poco especificos mediante las mismas alternativas de...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
awagner-mainz/notebooks	gallery/DHD2019_Azpilcueta.ipynb	mit	[ "Multimodale Versuche der Alignierung historischer Texte\nAndreas Wagner und Manuela Bragagnolo, Max-Planck-Institut für europäische Rechtsgeschichte, Frankfurt/M.\n<wagner@rg.mpg.de> <bragagno&...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
natronics/rust-fc	analysis/results.ipynb	gpl-3.0	[ "Comparing rust-fc To Simulation Output\nThe simulator proccessing code adds realisic noise to the IMU input before sending it to rust-fc.\nWe'll compare the clean \"ideal\" simulator numbers to what was actually received by rust-fc", "import psas_packet\nfrom psas_packet.io import BinFile\nimport csv\nimport mat...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
gaufung/Data_Analytics_Learning_Note	DesignPattern/BridgePattern.ipynb	mit	[ "桥梁模式(Bridge Pattern) \n1 代码\n在一个画图程序中，常会见到这样的情况：有一些预设的图形，如矩形、圆形等，还有一个对象-画笔，调节画笔的类型（如画笔还是画刷，还是毛笔效果等）并设定参数（如颜色、线宽等），选定图形，就可以在画布上画出想要的图形了。要实现以上需求，先从最抽象的元素开始设计，即形状和画笔（暂时忽略画布，同时忽略画笔参数，只考虑画笔类型）。", "class Shape(object):\n name=\"\"\n param=\"\"\n def __init__(self,*param):\n pass\n def getName(self)...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
joelowj/Udacity-Projects	Udacity-Deep-Learning-Foundation-Nanodegree/Project-4/dlnd_language_translation.ipynb	apache-2.0	[ "Language Translation\nIn this project, you’re going to take a peek into the realm of neural network machine translation. You’ll be training a sequence to sequence model on a dataset of English and French sentences that can translate new sentences from English to French.\nGet the Data\nSince translating the whole ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
vallis/libstempo	demo/libstempo-demo.ipynb	mit	[ "libstempo tutorial: basic functionality\nMichele Vallisneri, vallis@vallis.org; latest revision: 2016/10/12 for v2.3 revision", "%matplotlib inline\n%config InlineBackend.figure_format = 'retina'\n\nfrom __future__ import print_function\nimport sys, math, numpy as N, matplotlib.pyplot as P", "Load the libstemp...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
mne-tools/mne-tools.github.io	0.12/_downloads/plot_read_and_write_raw_data.ipynb	bsd-3-clause	[ "%matplotlib inline", "Reading and writing raw files\nIn this example, we read a raw file. Plot a segment of MEG data\nrestricted to MEG channels. And save these data in a new\nraw file.", "# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>\n#\n# License: BSD (3-clause)\n\nimport mne\nfrom m...	[ "code", "markdown", "code", "markdown", "code" ]
empet/Plotly-plots	Chord-diagram.ipynb	gpl-3.0	[ "Plotly plot of chord diagrams\nCircular layout or Chord diagram is a method of visualizing data that describe relationships. It was intensively promoted through Circos, a software package in Perl that was initially designed for displaying genomic data.\nThis 2013 stackoverflow question, whether there is a Pyth...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
Kaggle/learntools	notebooks/ml_intermediate/raw/tut3.ipynb	apache-2.0	[ "In this tutorial, you will learn what a categorical variable is, along with three approaches for handling this type of data.\nIntroduction\nA categorical variable takes only a limited number of values. \n\nConsider a survey that asks how often you eat breakfast and provides four options: \"Never\", \"Rarely\", \"...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
radu941208/DeepLearning	Intro_to_Neural_Networks/Building+your+Deep+Neural+Network+-+Step+by+Step+v5.ipynb	mit	[ "Building your Deep Neural Network: Step by Step\nWelcome to your week 4 assignment (part 1 of 2)! You have previously trained a 2-layer Neural Network (with a single hidden layer). This week, you will build a deep neural network, with as many layers as you want!\n\nIn this notebook, you will implement all the func...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
cliburn/sta-663-2017	homework/05_Making_Python_Faster_Solutions.ipynb	mit	[ "%matplotlib inline\n%load_ext Cython\n\nimport math\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom sklearn.datasets import make_blobs \nfrom numba import jit, vectorize, float64, int64\n\nsns.set_context('notebook', font_scale=1.5)\n\n! conda update --yes numba", "Making Python...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
GoogleCloudPlatform/vertex-ai-samples	community-content/tf_agents_bandits_movie_recommendation_with_kfp_and_vertex_sdk/mlops_pipeline_tf_agents_bandits_movie_recommendation/mlops_pipeline_tf_agents_bandits_movie_recommendation.ipynb	apache-2.0	[ "# Copyright 2021 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "cod...
Unidata/unidata-python-workshop	notebooks/Surface_Data/Surface Data with Siphon and MetPy.ipynb	mit	[ "<a name=\"top\"></a>\n<div style=\"width:1000 px\">\n\n<div style=\"float:right; width:98 px; height:98px;\">\n<img src=\"https://raw.githubusercontent.com/Unidata/MetPy/master/metpy/plots/_static/unidata_150x150.png\" alt=\"Unidata Logo\" style=\"height: 98px;\">\n</div>\n\n<h1>Working with Surface Observations i...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
calico/basenji	manuscripts/akita/tutorial.ipynb	apache-2.0	[ "Required inputs for Akita are:\n* binned Hi-C or Micro-C data stored in cooler format (https://github.com/mirnylab/cooler)\n* Genome FASTA file\nFirst, make sure you have a FASTA file available consistent with genome used for the coolers. Either add a symlink for a the data directory or download the machine learni...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
balmandhunter/jupyter-tips-and-tricks	notebooks/04-More_basics.ipynb	mit	[ "Jupyter Notebook Basics", "names = ['alice', 'jonathan', 'bobby']\nages = [24, 32, 45]\nranks = ['kinda cool', 'really cool', 'insanely cool']\n\nfor (name, age, rank) in zip(names, ages, ranks):\n print name, age, rank\n\nfor index, (name, age, rank) in enumerate(zip(names, ages, ranks)):\n print index, n...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
tensorflow/docs	site/en/tutorials/images/cnn.ipynb	apache-2.0	[ "Copyright 2019 The TensorFlow Authors.", "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
dsteurer/cs4814fa15	turing/turing.ipynb	mit	[ "%run -i turing.py\ninit()", "Turing machine computation\nTape\nWe will represent the tape as a list of tape symbols and we will represent tape symbols as Python strings.\nThe string ' ' represents the blank symbol.\nThe string '\|>' represents the start symbol, which indicates the beginning of the tape.\nState...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
mne-tools/mne-tools.github.io	stable/_downloads/64e3b6395952064c08d4ff33d6236ff3/evoked_whitening.ipynb	bsd-3-clause	[ "%matplotlib inline", "Whitening evoked data with a noise covariance\nEvoked data are loaded and then whitened using a given noise covariance\nmatrix. It's an excellent quality check to see if baseline signals match\nthe assumption of Gaussian white noise during the baseline period.\nCovariance estimation and dia...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
gutouyu/cs231n	cs231n/assignment/assignment2/TensorFlow.ipynb	mit	[ "What's this TensorFlow business?\nYou've written a lot of code in this assignment to provide a whole host of neural network functionality. Dropout, Batch Norm, and 2D convolutions are some of the workhorses of deep learning in computer vision. You've also worked hard to make your code efficient and vectorized.\nFo...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
pfschus/fission_bicorrelation	methods/build_det_df_angles_pairs.ipynb	mit	[ "<h1 id=\"tocheading\">Table of Contents</h1>\n<div id=\"toc\"></div>", "%%javascript\n$.getScript('https://kmahelona.github.io/ipython_notebook_goodies/ipython_notebook_toc.js')", "Chi-Nu Array Detector Angles\nAuthor: Patricia Schuster\nDate: Fall 2016/Winter 2017\nInstitution: University of Michigan NERS\nEm...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
InsightSoftwareConsortium/SimpleITK-Notebooks	Python/02_Pythonic_Image.ipynb	apache-2.0	[ "Pythonic Syntactic Sugar <a href=\"https://mybinder.org/v2/gh/InsightSoftwareConsortium/SimpleITK-Notebooks/master?filepath=Python%2F02_Pythonic_Image.ipynb\"><img style=\"float: right;\" src=\"https://mybinder.org/badge_logo.svg\"></a>\nThe Image Basics Notebook was straight forward and closely follows ITK's C++ ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
WMD-group/SMACT	examples/Inverse_perovskites/Inverse_formate_perovskites.ipynb	mit	[ "Formate perovskites\nPerovskites are an important class of inorganic materials, particularly for solar energy applications.\nUsually, the perovskite structure contains an A cation, a B cation and an C anion in the ratio 1:1:3 (black, blue and red in the figure below, respectively, see wikipeidia for more informati...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
StingraySoftware/notebooks	Simulator/Lag Analysis.ipynb	mit	[ "Contents\nThis notebook analyses lag-frequency spectrums of the light curves simulated through impulse response approach. First, a simple case with delta impulse response is covered. Subsequently, an energy-dependent impulse response scenario is analysed.\nSetup\nImport some useful libraries.", "import numpy as ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
dereneaton/ipyrad	newdocs/API-analysis/cookbook-vcf2hdf5.ipynb	gpl-3.0	[ "<span style=\"color:gray\">ipyrad-analysis toolkit:</span> vcf_to_hdf5\nView as notebook\nMany genome assembly tools will write variant SNP calls to the VCF format (variant call format). This is a plain text file that stores variant calls relative to a reference genome in tabular format. It includes a lot of addit...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
Unidata/MetPy	talks/MetPy Exercise.ipynb	bsd-3-clause	[ "from datetime import datetime, timedelta\nfrom siphon.catalog import TDSCatalog\nfrom siphon.ncss import NCSS\nimport numpy as np\nimport metpy.calc as mpcalc\nfrom metpy.units import units, concatenate\nfrom metpy.plots import SkewT", "Just some helper code to make things easier. metpy_units_handler plugins int...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "cod...
james-prior/cohpy	20160826-dojo-regex-travis.ipynb	mit	[ "from __future__ import print_function\nimport re", "Let's start with the original regular expression and\nstring to search from Travis'\nregex problem.", "pattern = re.compile(r\"\"\"\n (?P<any>any4?) # \"any\"\n ...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
ShantanuKamath/PythonWorkshop	2. Python Advanced.ipynb	mit	[ "Python Advanced\nDisclaimer - This document is only meant to serve as a reference for the attendees of the workshop. It does not cover all the concepts or implementation details discussed during the actual workshop.\n\nVariable Scope\nWhen you program, you'll often find that similar ideas come up again and again. ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
fcollonval/coursera_data_visualization	Making_Data_Management.ipynb	mit	[ "Assignment: Making Data Management Decisions - Python\nFollowing is the Python program I wrote to fulfill the third assignment of the Data Management and Visualization online course.\nI decided to use Jupyter Notebook as it is a pretty way to write code and present results.\nResearch question\nUsing the Gapminder ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
amueller/advanced_training	05.1 Trees and Forests.ipynb	bsd-2-clause	[ "Trees and Forests", "%matplotlib notebook\nfrom preamble import *", "Decision Tree Classification", "from plots import plot_tree_interactive\nplot_tree_interactive()", "Random Forests", "from plots import plot_forest_interactive\nplot_forest_interactive()\n\nfrom sklearn.ensemble import RandomForestClass...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
Jwuthri/Mozinor	mozinor/example/Mozinor example Class.ipynb	mit	[ "Use mozinor for classification\nImport the main module", "from mozinor.baboulinet import Baboulinet", "Prepare the pipeline\n(str) filepath: Give the csv file\n(str) y_col: The column to predict\n(bool) regression: Regression or Classification ?\n(bool) process: (WARNING) apply some preprocessing on your data ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
danresende/deep-learning	autoencoder/Convolutional_Autoencoder.ipynb	mit	[ "Convolutional Autoencoder\nSticking with the MNIST dataset, let's improve our autoencoder's performance using convolutional layers. Again, loading modules and the data.", "%matplotlib inline\n\nimport numpy as np\nimport tensorflow as tf\nimport matplotlib.pyplot as plt\n\nfrom tensorflow.examples.tutorials.mnis...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
avtlearns/automatic_text_summarization	TextRank_Automatic_Summarization_for_Medical_Articles.ipynb	gpl-3.0	[ "Automatic Summarization of Medical Articles\nAuthor: Abhijit V Thatte\nSolution: We will use TextRank for automatic summarization of medical articles. NIH's (National Institues for Health) PubMed repository consists of links to hundreds of thousands of medical articles. We will use articles relevant to various typ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
mne-tools/mne-tools.github.io	0.24/_downloads/b7659d33d6ffe8531d004e9d6051f16f/forward_sensitivity_maps.ipynb	bsd-3-clause	[ "%matplotlib inline", "Display sensitivity maps for EEG and MEG sensors\nSensitivity maps can be produced from forward operators that\nindicate how well different sensor types will be able to detect\nneural currents from different regions of the brain.\nTo get started with forward modeling see tut-forward.", "#...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
phungkh/phys202-2015-work	assignments/assignment05/InteractEx03.ipynb	mit	[ "Interact Exercise 3\nImports", "%matplotlib inline\nfrom matplotlib import pyplot as plt\nimport numpy as np\n\nfrom IPython.html.widgets import interact, interactive, fixed\nfrom IPython.display import display", "Using interact for animation with data\nA soliton is a constant velocity wave that maintains its ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
CalPolyPat/Python-Workshop	Python Workshop/Containers.ipynb	mit	[ "Containers\nContainers are set of objects including lists, sets, tuples, and dictionaries. They hold other variables in various different ways following different rules. These are arguably the most used, and most useful, objects you will encounter in today's course.\nLists\nLists are objects that hold variables in...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
Jim00000/Numerical-Analysis	2_Systems_Of_Equations.ipynb	unlicense	[ "CHAPTER 2 - Systems Of Equations", "# Import modules\nimport sys\nimport numpy as np\nimport numpy.linalg\nimport scipy\nimport sympy\nimport sympy.abc\nfrom scipy import linalg\nfrom scipy.sparse import linalg as slinalg", "2.1 Gaussian Elimination", "def naive_gaussian_elimination(matrix):\n \"\"\"\n ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
jeicher/cobrapy	documentation_builder/solvers.ipynb	lgpl-2.1	[ "Solver Interface\nEach cobrapy solver must expose the following API. The solvers all will have their own distinct LP object types, but each can be manipulated by these functions. This API can be used directly when implementing algorithms efficiently on linear programs because it has 2 primary benefits:\n\n\nAvoid ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
kfollette/ASTR200-Spring2017	Labs/Lab9/Lab 9.ipynb	mit	[ "Names: [Insert Your Names Here]\nLab 9 - Data Investigation 1 (Week 1) - Educational Research Data\nLab 9 Contents\n\nBackground Information\nIntro to the Second Half of the Class\nIntro to Dataset 1: The Quantitative Reasoning for College Science Assessment\nInvestigating Tabular Data with Pandas\nReading in and ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
weikang9009/pysal	notebooks/explore/spaghetti/Spaghetti_Pointpatterns_Empirical.ipynb	bsd-3-clause	[ "$SPA$tial $G$rap$H$s: n$ET$works, $T$opology, & $I$nference\nTutorial for pysal.spaghetti: Working with point patterns: empirical observations\nJames D. Gaboardi [jgaboardi@fsu.edu]\n\nInstantiating a pysal.spaghetti.Network\nAllocatin...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
jldinh/multicell	examples/06 - Growth and divisions.ipynb	mit	[ "Preparation", "%matplotlib notebook", "Imports", "import multicell\nimport numpy as np", "Problem definition\nSimulation and tissue structure", "sim = multicell.simulation_builder.generate_cell_grid_sim(20, 20, 1, 1e-3)", "Tissue growth\nWe first enable growth and specify the number of growth steps to ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
barakovic/COMMIT	doc/tutorials/AdvancedSolvers/tutorial_solvers.ipynb	gpl-3.0	[ "You can find the text version of this tutorial at this link.\nAdvanced solvers\nThis tutorial shows how to exploit the advanced features of the COMMIT framework from the side of the optimisation problem. The general formulation is the following:\n\\begin{equation}\nx^ = \\arg\\min_{x\\in R^n_+} \\frac12 \\\|Ax-y\\\|...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
darkomen/TFG	medidas/20072015/FILAEXTRUDER/.ipynb_checkpoints/Analisis-checkpoint.ipynb	cc0-1.0	[ "Análisis de los datos obtenidos\nProducción del día 20 de Julio de 2015\nLos datos del experimento:\n* Hora de inicio: 16:08\n* Hora final : 16:35 \n* $T: 150ºC$\n* $V_{min} tractora: 1 mm/s$\n* $V_{max} tractora: 3 mm/s$\nSe desea comprobar si el filamento que podemos llegar a extruir con el sistema de la tractor...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
barbagroup/JITcode-MechE	module00_Introduction_to_Python/01_Lesson01_Playing_with_data.ipynb	mit	[ "Version 0.1 -- February 2014\nJITcode 1, lesson 1\nThis is lesson 1 of the first Just-in-Time (JIT) module for teaching computing to engineers, in context. The first module lays the foundations for building computational skills. It is not meant to support a particular engineering course, so it can be used by fresh...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
amueller/nyu_ml_lectures	Unsupervised Transformers.ipynb	bsd-2-clause	[ "%matplotlib nbagg\nimport matplotlib.pyplot as plt\nimport numpy as np", "<img src=\"figures/unsupervised_workflow.svg\" width=100%>", "from sklearn.datasets import load_digits\nfrom sklearn.cross_validation import train_test_split\nimport numpy as np\nnp.set_printoptions(suppress=True)\n\ndigits = load_digits...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "cod...
pelson/python-stratify	INTRO.ipynb	bsd-3-clause	[ "Stratify\nVertical interpolation for numerical weather prediction (NWP) model data\nWhilst this is not the only use for the stratify package, NWP vertical interpolation was the motivating usecase for the package's creation.\nIn its simplest form, vertical interpolation ammounts to a 1d interpolation at each grid-p...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
John-Keating/ThinkStats2	code/chap04ex.ipynb	gpl-3.0	[ "Exercise from Think Stats, 2nd Edition (thinkstats2.com)<br>\nAllen Downey\nRead the pregnancy file.", "%matplotlib inline\n\nimport nsfg\npreg = nsfg.ReadFemPreg()", "Select live births, then make a CDF of <tt>totalwgt_lb</tt>.", "import thinkstats2 as ts\n\nlive = preg[preg.outcome == 1]\n\nwgt_cdf = ts.Cd...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
evgeniiegorov/evgeniiegorov.github.io	_posts/Seminar+5+Trees+Bagging+%28with+Solutions%29.ipynb	mit	[ "Seminar 5: Tree and Bootstrap Aggregation\nCourse: MA06018, Machine Learning by professor Evgeny Burnaev <br>\nAuthor: Evgenii Egorov\nTable of contents:\n\nTree\nSimple Stamp\nLimitations of trees\n\n\nBagging\nBootstrap\nRandom Forest", "import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
feststelltaste/software-analytics	notebooks/Generating Synthetic Data based on a Git Log.ipynb	gpl-3.0	[ "Context\nOften, it isn't possible to get the real data where we applied our analysis. In these cases, we can generate similar dataset that contain similar phenomena based on real data. This notebook shows an example about how we can do it.\nGet base data\nThe data, we want to derive another dataset. It's just ther...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
mspcvsp/cincinnati311Data	ClusterServiceCodes.ipynb	gpl-3.0	[ "Setup Code Environment", "import csv\nimport re\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport nltk\nfrom sklearn.cluster import KMeans\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.metrics.pairwise import cosine_similarity\nfrom collections import defaultdict\nimport s...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
jorisvandenbossche/2015-EuroScipy-pandas-tutorial	solved - 02 - Data structures.ipynb	bsd-2-clause	[ "import pandas as pd\n\n%matplotlib inline\nimport numpy as np\nimport matplotlib.pyplot as plt\ntry:\n import seaborn\nexcept ImportError:\n pass", "Tabular data", "df = pd.read_csv(\"data/titanic.csv\")\n\ndf.head()", "Starting from reading this dataset, to answering questions about this data in a few...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "cod...
quantopian/research_public	notebooks/lectures/Spearman_Rank_Correlation/questions/notebook.ipynb	apache-2.0	[ "Exercises: Spearman Rank Correlation\nLecture Link\nThis exercise notebook refers to this lecture. Please use the lecture for explanations and sample code.\nhttps://www.quantopian.com/lectures#Spearman-Rank-Correlation\nPart of the Quantopian Lecture Series:\n\nwww.quantopian.com/lectures\ngithub.com/quantopian/re...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
UCBerkeleySETI/breakthrough	GBT/pulsar_searches/Pulsar_Search/Pulsar_DedisperseV3.ipynb	gpl-3.0	[ "Pulsar Folding and Searching\nBy Peter Ma\nPulsar searching is a very compute-intensive task. Searching for repeating signals within noisy data is difficult because pulses tend to have a low signal to noise ratio. Our goal is to process, clean, identify potential periods, and fold the pulses to increase the SNR. T...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
regisDe/compagnons	Calcul symbolique.ipynb	gpl-2.0	[ "Calcul symbolique en Python", "%matplotlib inline", "Introduction\nCe notebook est la traduction française du cours sur SymPy disponible entre autre sur Wakari avec quelques modifications et compléments notamment pour la résolution d'équations différentielles. Il a pour but de permettre aux étudiants de différ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
jpilgram/phys202-2015-work	assignments/midterm/AlgorithmsEx03.ipynb	mit	[ "Algorithms Exercise 3\nImports", "%matplotlib inline\nfrom matplotlib import pyplot as plt\nimport numpy as np\n\nfrom IPython.html.widgets import interact", "Character counting and entropy\nWrite a function char_probs that takes a string and computes the probabilities of each character in the string:\n\nFirst...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
wtsi-medical-genomics/team-code	python-club/notebooks/regular-expressions.ipynb	gpl-2.0	[ "import re # Python's regular expression module\n\ndef re_test(regex, query):\n \"\"\"A helper function to test if a regex has a match in a query.\"\"\"\n p = re.compile(regex)\n result = 'MATCH' if p.match(query) else 'NOT FOUND'\n print '\"{}\" with regex \"{}\": {}'.format(query, regex, result)", "...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "cod...
janusnic/21v-python	unit_20/parallel_ml/rendered_notebooks/06 - Distributed Model Selection and Assessment.ipynb	mit	[ "Distributed Model Selection and Assessment\nOutline of the session:\n\nIntroduction to IPython.parallel\nSharing Data Between Processes with Memory Mapping\nParallel Grid Search and Model Selection\nParallel Computation of Learning Curves (TODO)\nDistributed Computation on EC2 Spot Instances with StarCluster\n\nMo...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
rishuatgithub/MLPy	nlp/UPDATED_NLP_COURSE/00-Python-Text-Basics/00-Working-with-Text-Files.ipynb	apache-2.0	[ "<a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>\n\nWorking with Text Files\nIn this section we'll cover\n * Working with f-strings (formatted string literals) to format printed text\n * Working with Files - opening, reading, writing and appending text files\nFormatted String Litera...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
linglaiyao1314/maths-with-python	04-basic-plotting.ipynb	mit	[ "Plotting\nThere are many Python plotting libraries depending on your purpose. However, the standard general-purpose library is matplotlib. This is often used through its pyplot interface.", "from matplotlib import pyplot\n%matplotlib inline", "The command %matplotlib inline is not a Python command, but an IPyt...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
robertoalotufo/ia898	master/tutorial_contraste_iterativo_2.ipynb	mit	[ "Table of Contents\n<p><div class=\"lev1 toc-item\"><a href=\"#Realce-de-Contraste-Interativo-utilizando-Janela-e-Nível\" data-toc-modified-id=\"Realce-de-Contraste-Interativo-utilizando-Janela-e-Nível-1\"><span class=\"toc-item-num\">1  </span>Realce de Contraste Interativo utilizando Janela e Nível</a><...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
gogartom/caffe-textmaps	examples/classification.ipynb	mit	[ "Classifying ImageNet: the instant Caffe way\nCaffe has a Python interface, pycaffe, with a caffe.Net interface for models. There are both Python and MATLAB interfaces. While this example uses the off-the-shelf Python caffe.Classifier interface there is also a MATLAB example at matlab/caffe/matcaffe_demo.m.\nBefore...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
DS-100/sp17-materials	sp17/hw/hw1/hw1.ipynb	gpl-3.0	[ "Homework 1: Setup and (Re-)Introduction to Python\nCourse Policies\nHere are some important course policies. These are also located at\nhttp://www.ds100.org/sp17/.\nTentative Grading\nThere will be 7 challenging homework assignments. Homeworks must be completed\nindividually and will mix programming and short answ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
ES-DOC/esdoc-jupyterhub	notebooks/nerc/cmip6/models/hadgem3-gc31-hh/land.ipynb	gpl-3.0	[ "ES-DOC CMIP6 Model Properties - Land\nMIP Era: CMIP6\nInstitute: NERC\nSource ID: HADGEM3-GC31-HH\nTopic: Land\nSub-Topics: Soil, Snow, Vegetation, Energy Balance, Carbon Cycle, Nitrogen Cycle, River Routing, Lakes. \nProperties: 154 (96 required)\nModel descriptions: Model description details\nInitialized From: -...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
dotsdl/msmbuilder	examples/hmm-and-msm.ipynb	lgpl-2.1	[ "This example builds HMM and MSMs on the alanine_dipeptide dataset using varing lag times\nand numbers of states, and compares the relaxation timescales", "from __future__ import print_function\nimport os\n%matplotlib inline\nfrom matplotlib.pyplot import *\nfrom msmbuilder.featurizer import SuperposeFeaturizer\n...	[ "markdown", "code", "markdown", "code", "markdown", "code" ]
GoogleCloudPlatform/vertex-ai-samples	notebooks/community/pipelines/google_cloud_pipeline_components_TPU_model_train_upload_deploy.ipynb	apache-2.0	[ "# Copyright 2021 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "cod...
mari-linhares/tensorflow-workshop	code_samples/RNN/sentiment_analysis/.ipynb_checkpoints/SentimentAnalysis-batch_64-checkpoint.ipynb	apache-2.0	[ "Dependencies", "# Tensorflow\nimport tensorflow as tf\nprint('Tested with TensorFLow 1.2.0')\nprint('Your TensorFlow version:', tf.__version__) \n\n# Feeding function for enqueue data\nfrom tensorflow.python.estimator.inputs.queues import feeding_functions as ff\n\n# Rnn common functions\nfrom tensorflow.contrib...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
jamesnw/wtb-data	notebooks/Colors.ipynb	mit	[ "Everyone's favorite nerdy comic, XKCD, ranked colors by best tasting. I thought I would use the WTB dataset to compare and see if the data agrees.", "# Import libraries\nimport numpy as np\nimport pandas as pd\n# Import the data\nimport WTBLoad\nwtb = WTBLoad.load_frame()\n\npink = [\"watermelon\", \"cranberry\"...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
gunan/tensorflow	tensorflow/lite/micro/examples/hello_world/create_sine_model.ipynb	apache-2.0	[ "Copyright 2019 The TensorFlow Authors.", "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
fonnesbeck/ngcm_pandas_2016	notebooks/1.4 - Pandas Best Practices.ipynb	cc0-1.0	[ "Idomatic Pandas\n\nQ: How do I make my pandas code faster with parallelism?\nA: You don’t need parallelism, you can use Pandas better.\n-- Matthew Rocklin\n\nNow that we have been exposed to the basic functionality of pandas, lets explore some more advanced features that will be useful when addressing more complex...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
anandha2017/udacity	nd101 Deep Learning Nanodegree Foundation/notebooks/1 - playing with jupyter/keyboard-shortcuts.ipynb	mit	[ "Keyboard shortcuts\nIn this notebook, you'll get some practice using keyboard shortcuts. These are key to becoming proficient at using notebooks and will greatly increase your work speed.\nFirst up, switching between edit mode and command mode. Edit mode allows you to type into cells while command mode will use ke...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
kkkddder/dmc	notebooks/week-6/02-using a pre-trained model with Keras.ipynb	apache-2.0	[ "Lab 6.2 - Using a pre-trained model with Keras\nIn this section of the lab, we will load the model we trained in the previous section, along with the training data and mapping dictionaries, and use it to generate longer sequences of text.\nLet's start by importing the libraries we will be using:", "import numpy ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
feststelltaste/software-analytics	notebooks/Committer Distribution.ipynb	gpl-3.0	[ "Introduction\nIn the last notebook, I showed you how easy it is to connect jQAssistant/neo4j with Python Pandas/py2neo. In this notebook, I show you a (at first glance) simple analysis of the Git repository https://github.com/feststelltaste/spring-petclinic. This repository is a fork of the demo repository for jQA...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
jedludlow/sp-for-ds	sp_for_ds.ipynb	mit	[ "%matplotlib widget\n\nimport warnings; warnings.simplefilter('ignore')\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport pandas as pd\nimport scipy.signal as signal\nimport ipywidgets as widgets\nfrom IPython.display import display\nsns.set_context('notebook')", "<hr>\n\nSigna...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
scikit-optimize/scikit-optimize.github.io	0.7/notebooks/auto_examples/strategy-comparison.ipynb	bsd-3-clause	[ "%matplotlib inline", "Comparing surrogate models\nTim Head, July 2016.\nReformatted by Holger Nahrstaedt 2020\n.. currentmodule:: skopt\nBayesian optimization or sequential model-based optimization uses a surrogate\nmodel to model the expensive to evaluate function func. There are several\nchoices for what kind ...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
sdss/marvin	docs/sphinx/jupyter/first-steps.ipynb	bsd-3-clause	[ "First Steps\nNow that you have installed Marvin, it's time to take your first steps. If you want to learn more about how Marvin works, then go see General Info to learn about Marvin Modes, Versions, or Downloading. If you just want to play, then read on.\nFirst let's run some boilerplate code for Python 2/3 comp...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
ctroupin/CMEMS_INSTAC_Training	PythonNotebooks/PlatformPlots/Plot_TimeSeries1.ipynb	mit	[ "%matplotlib inline\nimport netCDF4\nimport matplotlib.pyplot as plt\nimport matplotlib as mpl\nfrom matplotlib import dates\nimport numpy as np", "Read variables and units\nWe assume the data file is present in the following directory:", "datafile = \"~/CMEMS_INSTAC/INSITU_MED_NRT_OBSERVATIONS_013_035/history/...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
heatseeknyc/data-science	src/bryan analyses/Hack for Heat #1.ipynb	mit	[ "Hacking for heat\nIn this series, I'm going to be posting about the process that goes on behind some of the blog posts we end up writing. In this first entry, I'm going to be exploring a number of datsets.\nThese are the ones that I'm going to be looking at:\n\nHPD (Housing Preservation and Development) housing li...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
arcyfelix/Courses	17-09-17-Python-for-Financial-Analysis-and-Algorithmic-Trading/05-Pandas-with-Time-Series/01 - Datetime Index.ipynb	apache-2.0	[ "<a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>\n\n<center>Copyright Pierian Data 2017</center>\n<center>For more information, visit us at www.pieriandata.com</center>\nIntroduction to Time Series with Pandas\nA lot of our financial data will have a datatime index, so let's learn h...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
harmsm/pythonic-science	chapters/00_inductive-python/05_lists.ipynb	unlicense	[ "Lists\nLists are objects that let you hold on to multiple values at once in a sane and organized fashion.\nIntroduction\nLists are ordered collections of objects. Objects in lists can be of any type. You can also add and remove list entries. They are indicated by \"[\" and \"]\" brackets.\nmy_list = [1,2,3]\nIn...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
azhurb/deep-learning	sentiment_network/Sentiment Classification - How to Best Frame a Problem for a Neural Network (Project 4).ipynb	mit	[ "Sentiment Classification & How To \"Frame Problems\" for a Neural Network\nby Andrew Trask\n\nTwitter: @iamtrask\nBlog: http://iamtrask.github.io\n\nWhat You Should Already Know\n\nneural networks, forward and back-propagation\nstochastic gradient descent\nmean squared error\nand train/test splits\n\nWhere to Get ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
mwickert/SP-Comm-Tutorial-using-scikit-dsp-comm	tutorial_part1/FIR Filter Design and C Headers.ipynb	bsd-2-clause	[ "%pylab inline\n#%matplotlib qt\nfrom __future__ import division # use so 1/2 = 0.5, etc.\nimport sk_dsp_comm.sigsys as ss\nimport sk_dsp_comm.fir_design_helper as fir_d\nimport sk_dsp_comm.coeff2header as c2h\nimport scipy.signal as signal\nimport imp # for module development and reload()\nfrom IPython.display imp...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
authman/DAT210x	Module5/Module5 - Lab4.ipynb	mit	[ "DAT210x - Programming with Python for DS\nModule5- Lab4", "import math\nimport numpy as np\nimport pandas as pd\n\nimport matplotlib.pyplot as plt\nimport matplotlib\n\nfrom sklearn import preprocessing\nfrom sklearn.decomposition import PCA\n\n# You might need to import more modules here..\n# .. your code here ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...
dani-lbnl/2017_ucberkeley_course	code/ZeissMicroscopyCenter2017_DaniUshizima_lecture.ipynb	gpl-3.0	[ "Image exploration using Python - essentials\n\nRead image from web\nQuerying image: matrix, sub-matrices, ROI\nImage transformations: filtering\nImmunohistochemistry example from scikit-image\nSegmentation and feature extraction \nSave information as a xls file \nSimulating 2D images - \"cells\"\nSimulate particle...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
MachineLearningStudyGroup/Smart_Review_Summarization	ipynbs/Dynamic_Aspect_Extraction_Part_B.ipynb	mit	[ "Dynamic Aspect Extraction for camera Reviews Part B\nHan, Kehang (hkh12@mit.edu)\nAs a follow-up demonstration, this ipynb is focused on extracting aspects from datasets called AmazonReviews, which has much more reviews on cameras. \nSet up", "import json\nimport nltk\nimport string\n\nfrom srs.utilities import ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
BBN-Q/Auspex	doc/examples/Example-Channel-Lib.ipynb	apache-2.0	[ "Example Q2: Save and Loading Channel Library Versions\nThis example notebook shows how one may save and load versions of the channel library.\n© Raytheon BBN Technologies 2018\nSaving Channel Library Versions\nWe initialize the channel library as shown in tutorial Q1:", "from QGL import *\n\ncl = ChannelLibrary(...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
ikegwukc/INFO597-DeepLearning-GameTheory	basicGames/Basic Games.ipynb	mit	[ "Basic Games\nIterated Prisoner's Dilemma\nPrisoner's Dilemma is a pretty standard game that is commonly used in game theory (for a comprehensive defintion of Prisoner's dilemma see this link). Iterated Prisoner's Dilemma is simply repeating the game and allowing the agents to choose again. Prisoner's Dilemma is im...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "mar...

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