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# # Understanding E... | solutions/6_scipp/3_understanding-event-data.ipynb |
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# # Roll decay test parameter identification
# Various... | notebooks/rolldecay/studies/03.1_maa_roll_decay_test_system_identification.ipynb |
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# + [markdown] id="Ic4_occAAiAT"
# ##### Copyright 2019 The TensorFlow Author... | site/ja/tutorials/keras/text_classification.ipynb |
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import mne
from mne.datasets import testing
data_path = testing.data_path()
raw_fname = data_path + '/MEG/sample/sample_audvis_trunc_raw.fif'
... | mne/viz/_brain/tests/test.ipynb |
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# General imports, will clean up as required
impor... | General_Machine_Learning/Kaggle_Titanic/Titanic_XGBoost_Hyperparameters.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | PythonBootCamp.ipynb |
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# + deletable=true ... | notebooks/6.0-mmh-append_labels_to_df_for_logreg_and_svm.ipynb |
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# # AutoML Classification experime... | 2-training-and-interpretability/2.3-automl-training/remote-compute/binayclassification-employee-attrition-autoaml-remote-amlcompute.ipynb |
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# # Package loading and basic configurations
# +
# %l... | examples/mmateenm90- Asgn01.ipynb |
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from storms import *
import matplotlib.pyplot as plt
... | examples/Example 1 - Make storm.ipynb |
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# + [markdown] id="XN-8hEftfgeF"
# **Universidad Tecno... | 04_markov/casos_codigo/ioperativ_clase04_ejercicio06_markov_a_resolver.ipynb |
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# # Analyzing time series
#
# Although the Raven serve... | docs/source/notebooks/time_series_analysis.ipynb |
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# this script reads and plots wrf output... | Fig04.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | DS_Sprint_Challenge_21.ipynb |
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# # 6. Datan suodattimien vertailu
#
# Käytämme tehtäv... | Opetusmateriaalit/AvoinDataHiukkasfysiikassa/3_Data-analyysi/06_DatanSuodattimienVertailu.ipynb |
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# + [markdown] id="2JXWocLnz38N"
# You might need to i... | raw/kEffNet/Oxford-IIIT-Pet/JP30D11 - The Oxford-IIIT Pet Dataset - 224x224 150 Epochs - D6_32 - batch32.ipynb |
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# title: "Find Nearest Neighbors"
# author: "<NAME>"
# date: 2017-12-20T11:53:49-07:00
# description: "Find a observation's nearest neighbors in scikit-learn."
# type: technical_note
# draft: false
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# # 1. Fill the missing pieces of the `Calculator` cla... | notebooks/beginner/exercises/classes_exercise.ipynb |
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# # Data Visualization Exercise
#
# For this exercise,... | Module_4_Data_Visualization/Module_4_Exercise.ipynb |
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from cobs import cobs
import random
i... | notes/cobs_random.ipynb |
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import pandas as pd
import numpy as np
import mat... | Titanic_sub.ipynb |
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... | general/youtube-api/youtube-api.ipynb |
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# <div>
# <img src="../reports/gif/testing_gif.gif" wi... | notebooks/Untitled.ipynb |
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# # Assignment1 Day5
# +
def SubList(lis):
k=0
... | Assignment1D5.ipynb |
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# + active=""
# \tableofcontents
# % These TeX command... | docs/nb_examples/rs_fec_conv.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Genetic_Algorithm.ipynb |
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import pandas as pd
# ## Load data... | A6-final project.ipynb |
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def happynumbers(num):
t=num
c=0
def c... | Basics_Python/python7.ipynb |
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# ## Saving and loading objects
import sfsimodels as ... | examples/designing_a_foundation.ipynb |
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from itertools import zip_longest
names = ['Alice', '... | notebook/zip_longest_example.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Stock_price_prediction_using_MLP.ipynb |
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# # Recommendation Systems
#
# The class of web applic... | #0 Introduction.ipynb |
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# ## 10. Point set and Mask Transformation
# Tra... | examples/ITK_Example10_PointSetAndMaskTransformation.ipynb |
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# + [markdown] Collapsed="false" colab_typ... | docs/cookbooks/1-getting-started/0-Verifying-your-connection.ipynb |
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# # Advice for Programming Interview Questions: Focus ... | Programming-Python.ipynb |
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import tushare as ts
im... | quant/sample_code/tushare.ipynb |
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# In this notebook you will use composer a... | notebooks/medical_image_segmentation_composer.ipynb |
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import pandas as pd
import numpy as np
from sklearn.li... | regression-modeling.ipynb |
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# # 修饰符
# ## 函数是一种对象
# 在 `Python` 中，函数是也是一种对象。
# +
... | lijin-THU:notes-python/05-advanced-python/05.12-decorators.ipynb |
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# + [markdown] slideshow={"slide_type": "notes"}
# # M... | 2_minimal_example_optimization_task.ipynb |
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# # Post-APA calling: Imputat... | pipeline/apa_impute.ipynb |
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import numpy as np
import matplotlib.pyplot as plt... | gauss_derivation/moment_of_gauss.ipynb |
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# #### IRIS Unsupervised
# #### Name : <NAME>
# #### I... | Unsupervised IRIS/IRIS Unsupervised.ipynb |
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# + [markdown] id="Kgj2fjkxBWvA"
# # TITANIC SURVIVAL PREDICTION
# <p align="... | Datascience_With_Python/Machine Learning/Projects/Titanic Survival Prediction/titanic_survival_prediction.ipynb |
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# # Baseline examples
#
# <NAME>
#
# July 2017
#
#... | examples/.ipynb_checkpoints/Baseline_examples_2_withfakedata-checkpoint.ipynb |
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# # Compute county spread score
import numpy as np
im... | modeling/eda_raw_data/commute/02_compute_county_spread_score.ipynb |
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# +
#all_slow
# -
#export
import tempfile
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# # How to use this notebook ?
# * In the last cell, e... | Kinect_project/Kate library/Data parsing and feature creation.ipynb |
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# Copyright (c) Microsoft Corporation. All rights rese... | notebook/onnx-pipeline.ipynb |
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# + [markdown] id="OSSeL4ndX7mN"
# ## Using keras on MNIST dataset for image ... | Handwriting_Recognition_using_Mnist_dataset.ipynb |
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# # Figure 1: Exploratory data analysis
import pandas... | figures/Figure1_eda.ipynb |
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# Dependencies
from splinter import Browser
from bs4 i... | Missions_to_Mars/mission_to_mars.ipynb |
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# ### <div class="alert alert-success" style="backgrou... | Apache_Spark2.x - RDDs.ipynb |
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# ___
#
# <a href='http://www.pieriandata.com'><img sr... | Data Science Resources/Jose portila - ML/05-Seaborn/08-Seaborn-Exercise-Solutions.ipynb |
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# <a href="https://colab... | practice/machine-learning/practice/caltech_CNN_jpynb.ipynb |
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# <img width="10%"... | Twitter/Twitter_Post_text_and_image.ipynb |
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#activation function
def act(a... | NN_onelayer/Assignment7Question1ZelinLi.ipynb |
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def win():
print("win")
def lose():
print("los... | chapter2/homework/computer/5-17/201611580284.ipynb |
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import csv
pypollcsv = os.path.join("Resour... | PyPoll/PyPoll.ipynb |
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// + dotnet_interactive={"language": "cs... | doc/handbook/apdx-MPISolverPerformance/strongScaling/IBM_RotCube/Part1_0-Calculations_Minibatch.ipynb |
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# # Boxfill Tutorial
#
# This is an in-depth i... | docs/Jupyter/boxfill.ipynb |
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# # Modelo Provincias
# Santa Fe, Cordoba, Buenos air... | TP2-Predictor-Regresion-Lineal-Properati/Notebooks/Modelo provincias.ipynb |
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import pandas as pd
import glob as glob
# +
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# This notebook was prepared by [<NAME>](http://donnem... | stacks_queues/stack/stack_solution.ipynb |
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# # A basic part of speech tagger
# This tutorial wal... | python/examples/Learning_to_Search.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # <... | .ipynb_checkpoints/ch03-checkpoint.ipynb |
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# # ESnet SNMP REST API Connector
#
# This notebook de... | examples/tokio.connectors.esnet_snmp-demo.ipynb |
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# # Examen Final - Propedéutico de programación para l... | examen/ExamenFinal.ipynb |
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# # Classifying Fashion-MNIST
#
# This project uses th... | FromScratch/2_FashionMNIST/Fashion-MNIST.ipynb |
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import sys
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from typing import final
import... | part1/rough.ipynb |
# # 3.1. Teaching programming in the Notebook with IPython blocks
import time
from IPython.display import clear_output
from ipythonblocks import BlockGrid, colors
# + podoc={"output_text": "A IPython Blocks grid"}
grid = BlockGrid(width=5, height=5,
fill=colors['Purple'])
grid.show()
# + podoc={"out... | chapter03_notebook/01_blocks.ipynb |
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# # Comparing Common Crawl's Domain-Level Harmonic Cen... | cc-webgraph-statistics/comparison_domain_ranks.ipynb |
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# ### patters
# +
n=int(input())
i=1
while i<=n:
... | mix/3rd pattern1.ipynb |
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# # Using a previously trained tf model
# ## ... | Chapter 12 Utility Landscape/Chapter_12_Section_2_Loading_VGG_Model.ipynb |
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# # Testing DEMV on _Law School Admissions... | law.ipynb |
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# Variables
a = 5
a
# Reassign the variable
a = 10
... | 00-Python Object and Data Structure Basics/01-VariableAssigments.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
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import csv
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from dateti... | API14 R4S2 FINAL.ipynb |
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m, n = input().split()
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#include("defArc.jl")
type Arc
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# # User-Based Collaborative Filtering with Word2Vec
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# # What is Python?
#
# Python is an _general-purpose ... | Notebook 1 - Introduction to Python (Complete).ipynb |
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# # Expresiones y tipos predefinidos
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# # Segmenting and Clustering Neighborhoods in Toronto... | Week3/Submission/Segmenting and Clustering Neighborhoods in Toronto - Part 1.ipynb |
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# ##### Copyright 2021 The C-HACKMASTERS.
# +
... | Tutorial_notebooks/C-HACK_Tutorial_5_Regression.ipynb |
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# # Notes on Lesson 4
#
# <b>Tensors</b>
#
# <u>Ten... | _notebooks/2020-04-18-NotesOnLesson4.ipynb |
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// # Rust Environment Validation
//
// [![Open in SageMaker Studio Lab](https://stu... | custom-environments/Rust/env_validation.ipynb |
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# # 1. L1/L2 регуляризация
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# 1. У нас есть да... | seminar-3-l1l2/3_l1_l2_cv_nb.ipynb |
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# # Analyze A in Pareto
# +
from bokeh.plotting impor... | voltagebudget/ipynb/analyze_pareto.ipynb |