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#matplotlib inline
from __future__ import division... | data_and_code_for_figures/data_pickling_example/make_comparison_data_energy.ipynb |
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# + colab={"base_uri": "https://localhost:8080/", "hei... | 03_image_models/diagrams.ipynb |
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# # Beaver Triples
#
# Author:
# - <NAME> - [email](m... | Foundations_of_Private_Computation/Secure_multiparty_computation/Beaver Triples.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Keras_XOR_.ipynb |
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import sys,os
import numpy as np
import matplotlib.pyp... | Python_3/Jupyter/spatial_derivatives.ipynb |
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# # Lab 05: Linear module -- demo
import torch
import... | codes/labs_lecture04/lab01_linear_module/linear_module_demo.ipynb |
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# + tags=["remove-input", "active-ipynb", "remove-outp... | openmdao/docs/openmdao_book/theory_manual/setup_stack.ipynb |
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# + colab={} cola... | 01-Lesson-Plans/22-Big-Data/1/Activities/10-Stu_Pyspark_DataFrames_Dates/Unsolved/bigfoot.ipynb |
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# + tags=[]
import numpy as np
import yaml... | notebooks/Rubin Donut Demo.ipynb |
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# + [markdown] deletable=true editable=true
# # Calcul... | Compute Returns/calculate_returns.ipynb |
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# ### IMPORT LIBRARIES AS NUMPY AND PANDAS:
import nu... | Data Science and Machine Learning/Machine-Learning-In-Python-THOROUGH/EXAMPLES/PROJECT_EXAMPLES/01_Flight_Data_Cleaning/Flight_Dataset_Cleaning.ipynb |
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# + [markdown] id="uuAr0PR4P1Z4"
# <h2>Performing Basi... | hard_coding_tfidf.ipynb |
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# + id="PX6CfuJhjj4C" colab_type="code" colab={}
import numpy as np
import ma... | Dimensionality Reduction/Kernel_PCA_ipynb.ipynb |
# -*- coding: utf-8 -*-
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# # Project Proposal Group 15
#
# #### By: <NAME... | notebooks/Stat201Proposal_Draft.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="... | AAAI/Learnability/CIN/Linear/ds1/size_1000/synthetic_type0_Linear_m_5.ipynb |
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import itertools, functools
import numpy as np
# ### ... | 012319_hashing.ipynb |
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# # Anwendung 2: Topic Modeling
# Eine weitere Anwend... | 07_Topic_Modeling/Topic Modeling 20.ipynb |
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# -*- coding: utf-8 -*-
"""
This program makes le... | convert-jp-m-adapt4.ipynb |
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# # Multi-bin Poisson
# +
import logging
import json
... | docs/examples/notebooks/multiBinPois.ipynb |
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# # Updating the Tutorial Notebooks
# You can use the... | update-tutorials.ipynb |
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from rdkit import Chem
from multiprocessing import... | substructure_search.ipynb |
# + [markdown] colab_type="text" id="copyright-notice"
# #### Copyright 2017 Google LLC.
# + cellView="both" colab={"autoexec": {"startup": false, "wait_interval": 0}} colab_type="code" id="copyright-notice2"
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compli... | exercises/feature_crosses.ipynb |
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# + [markdown] _cell_guid="b1076dfc-b9ad-4... | notebooks/notebooks_to_review/manual-feature-engineering-by-will_075.ipynb |
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import tributary as t
from perspective import Perspect... | examples/pipeline_ws_http_sio.ipynb |
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# # Tutorial for *diskmap*
# This tutorial showcases ... | docs/tutorial.ipynb |
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# + language="javascript"
# function toggl... | notebooks/Untitled.ipynb |
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# + id="ur8xi4C7S06n"
# Copyright 2021 Google LLC
#
# Licensed under the Apac... | ai-platform-unified/notebooks/notebook_template.ipynb |
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# + [markdown] id="IkSguVy8Xv83"
# # **CycleGAN**
#
# ... | Colab_notebooks/CycleGAN_ZeroCostDL4Mic.ipynb |
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import tensorflow as tf
tf.enable_eager_execution... | Eager execution basics.ipynb |
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import pandas as pd
pd.set_option('display.max_colwidt... | notebooks/DataDictionary.ipynb |
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# # Patents
#
# This is patent data with UK inventors and applicants from PATSTAT
#
# **Warning**
#
# This data hasn't been explored yet so i... | notebooks/02_patents.ipynb |
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# ### Question 5 from Assignment: RegressionProblems
#... | Assignment6/hw6_RegressionProblems_q5.ipynb |
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# + [markdown] id="qSuUpkj1UuUa" colab_type="text"
# ### © Copyright 2020 [<N... | notebooks/old_notebooks/pretrain_transformer.ipynb |
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# + id="8b4tiMKzkA7e"
# Author <NAME>
# + id="ARAmpLtYeZd1"
# !pip install f... | Falconn_Test.ipynb |
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# # Length scale bounds
#
# <NAME>, September 2019.
#... | examples/Length scale bounds.ipynb |
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import numpy as np
import pandas as pd
from tqdm impor... | hotspot/code/dataTransform.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Midterm_Exam.ipynb |
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# # Introduction to Backtesting Algorithms
# ## By: <N... | 1. Introduction to Backtesting Algorithms.ipynb |
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# pip install requests
# pip install beautifulsoup... | requests.ipynb |
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# Before you begin, execute this cell to import numpy ... | coding_assignments/solutions/01_Classical_and_Quantum_Probability_Distributions.ipynb |
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import siibra
from nilearn import plotting
from IPytho... | 03-ProbabilisticAssignment.ipynb |
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# # COSIMA Cookbook... | ContributedExamples/COSIMA Cookbook.ipynb |
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# **UNIDAD 7**
# ### La Ciencia de Datos: Análisis, Mi... | AMV/AMV Unidad 7 Caso Practico.ipynb |
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# # 7장. 날짜와 시간 다루기
# 이 노트북을 주피터 노트북 뷰어(nb... | 07.ipynb |
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from my_package import mod2
from my_package.sub_packag... | notebook/import_example_relative.ipynb |
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repo_directory = '/Users/iaincarmichael/Dropbox/Re... | vertex_metrics_experiment/hospital_nlp.ipynb |
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#Imports
import sys
sys.path.append('../../')
fro... | JupyterNotebooks/Spark NLP/dictionary-sentiment.ipynb |
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# ## PDE
# The TTI wave equation for the square slown... | AcousticFWI/TTI_3d_simplified.ipynb |
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import numpy as np
import pandas as pd
import glob
DAT... | MakeDataSet.ipynb |
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# <script async src="https://www.googletagmanager.com/... | IllinoisGRMHD/doc/Tutorial-IllinoisGRMHD__Lorenz_psi6phi_rhs__add_gauge_terms_to_A_i_rhs.ipynb |
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# ## Read and plot near-real-time Wave Glider data
# ... | code/read_realtime_waveglider.ipynb |
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import pandas as pd
import numpy as np
from tqdm i... | DEEP LEARNING/NLP/BERD pretrained model/Named Entity Recognition With Bert.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | day_02/intro_to_python.ipynb |
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# ## Observations and Insights
#
# +
# Dependencies... | Pymaceuticals/pymaceuticals_starter.ipynb |
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#Modules to install via pip pandas,ipynb
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# # Tutorial of MendelEstimateFrequencies
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# ## ... | EstimateFrequencies.ipynb |
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# ## Day 22
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# https://adventofcode.com/2020/day/22
... | Day 22.ipynb |
# -*- coding: utf-8 -*-
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# # Ejemplo de uso de la b... | Memoria/capitulos/Ejemplo-uso-biblioteca.ipynb |
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# # Bias–variance tradeoff !!!
# 
# ### 현재 디렉토리가 smtm 프로젝트 ro... | notebook/upbit_data_provider_test.ipynb |
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# Copyright (c) 2022, salesforce.com, inc.
# All r... | pre-process/05-token_rule.ipynb |
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# default_exp models.layers
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# # Layers
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# > ... | nbs/100_models.layers.ipynb |
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# + [markdown] id="C-z71414BnfZ"
# # UX 2 Collecting D... | UX2_Collecting_Data.ipynb |
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# # Working with Data
# ## Loading data f... | module02_intermediate_python/02_04_working_with_files.ipynb |
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# # Vector manipulation in Python
#
# In this lab, you... | 1. Natural Language Processing with Classification and Vector Spaces/Week 4 Machine Translation and Document Search/Lab_1_Transforming vectors.ipynb |
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# ### To Train Object Detector
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#Clone the darknet r... | Object_detection/YoloV4.ipynb |
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# # Kinematics of a particle
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# <NAME>
# **Kinematic... | notebooks/KinematicsParticle.ipynb |
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# # Taylor Polynomial Approximations
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# <NAME>
#
# Cr... | calc-diffeq-analysis/taylor-series-standalone.ipynb |
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# # First TensorFlow Graphs
# In this notebook, we ex... | notebooks/live_training/first_tensorflow_graphs_LT.ipynb |
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# # Transport for London Cycle Data Exploration
#
# ## Dataset
# The data was provided from TFL and was retrieved from Kaggle: https://www.... | TFLCycles/data_exploration.ipynb |
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# + [markdown] id="zQBKILCUwz17"
# # Create a CNN to classify Cifar-10
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# Le... | ML/TinyML_Assignment_2_3_9_Question.ipynb |
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# Function Introspection
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#dummy code
i = 100
# ... | my_classes/FirstClassFunctions/finction-introspection.ipynb |
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# # Data Ninja - Secret places to open a restaurant (P... | OliveiraDataNinjaPartI.ipynb |
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#import pandas module
import pandas as pd
#create pa... | .ipynb_checkpoints/Untitled-checkpoint.ipynb |
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import cobra
import pandas as pd
import glob
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def... | Code/OldCode/OldCode_T6_Change_Media_and_Run_FBA.ipynb |
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# <a href="https://colab.research.googl... | scripts/test_train_demo_VideoDataFrame_colab.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # Import T... | GettingStarted/ImportTricks.ipynb |
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# ## Setting up
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import pandas as pd
from sklearn.... | .ipynb_checkpoints/data-cleaning-checkpoint.ipynb |
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# # Calculating values on total and net peak demand ch... | GridModel_GridImpact/MainPlotting/ReportedValuesInText/ReportedValues_peakchange.ipynb |
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# # PyVTK
# PyVTK is a Python library for creating f... | dataviz/PyVTK.ipynb |
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# default_exp gradientMethod
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# # Gradient Based Estimation
# $\hat{\alpha_i}$: the local dictCurve estimate for the $i^{th}$ bag
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#... | 09_Gradient_Method.ipynb |
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# # $\delta_F$-vs-$\rho_{DM}$
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import h5py
import ... | notebooks/MDM_Mtomo.ipynb |
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# + tags=[]
import numpy as np
import emcee
from matplotlib... | notebooks/basic_emcee_prototyping.ipynb |
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# ** This file gives a brief overview of the capabilit... | tutorial.ipynb |
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# ## Notebook generation
# This module contains the s... | docs_src/gen_doc.gen_notebooks.ipynb |
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from wordlist import secretWords
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# St... | semantle-helper.ipynb |
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import numpy as np
import matplotlib.pyplot as plt
d... | Damarad_Viktor/Integral.ipynb |
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# # Conditional and Slice Selection
import numpy as n... | Numpy - Conditional and Slice Selection.ipynb |
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# ## Implementing binary decision trees
# The goal of... | classification/Programming-And-Assignments/module-5-decision-tree-assignment-2-blank.ipynb |
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import pandas as pd
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filename='..... | utils/model.ipynb |
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import numpy as np
import matplotlib.pyplot as plt... | notebooks/Mesh.ipynb |
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# # Custom Analysis of Training Results
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# Notebook d... | examples/titanic/model_training_results.ipynb |
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# ## Prepare Features For Modeling: Create Training An... | ml_feature/05_Prepare_Features/05_01/Begin/05_01.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Vaksin_Sinovac_TextBlob_Sentiment_Analysis.ipynb |
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# # Advanced Lane Finding Project
#
# The goals / step... | Advance Lane Finding.ipynb |
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# <table>
# <tr>
# <td>Auhor:</td>
# ... | _tutorial_notebooks/Tutorial 3. toolbox_circuits.ipynb |
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# # Project 2: Predicting Catalog Demand
#
# **The Bus... | project-2/Predicting-catalog-demand.ipynb |