Datasets:

codeparrot
/

github-jupyter-parsed

repo_name stringlengths 6 77	path stringlengths 8 215	license stringclasses 15 values	cells sequence	types sequence
pk-ai/training	machine-learning/deep-learning/udacity/ud730/1_notmnist.ipynb	mit	[ "Deep Learning\nAssignment 1\nThe objective of this assignment is to learn about simple data curation practices, and familiarize you with some of the data we'll be reusing later.\nThis notebook uses the notMNIST dataset to be used with python experiments. This dataset is designed to look like the classic MNIST data...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
mattgiguere/doglodge	code/.ipynb_checkpoints/bf_qt_scraping-checkpoint.ipynb	mit	[ "bf_qt_scraping\nThis notebook describes how hotel data can be scraped using PyQT.\nThe items we want to extract are:\n- the hotels for a given city\n- links to each hotel page\n- text hotel summary\n- text hotel description\nOnce the links for each hotel are determined, I then want to extract the following items p...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
tritemio/multispot_paper	out_notebooks/usALEX-5samples-E-corrected-all-ph-out-12d.ipynb	mit	[ "Executed: Mon Mar 27 11:39:24 2017\nDuration: 7 seconds.\nusALEX-5samples - Template\n\nThis notebook is executed through 8-spots paper analysis.\nFor a direct execution, uncomment the cell below.", "ph_sel_name = \"None\"\n\ndata_id = \"12d\"\n\n# data_id = \"7d\"", "Load software and filenames definitions", ...	[ "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/multispot_paper	out_notebooks/usALEX-5samples-PR-raw-dir_ex_aa-fit-out-AexAem-17d.ipynb	mit	[ "Executed: Mon Mar 27 11:38:07 2017\nDuration: 10 seconds.\nusALEX-5samples - Template\n\nThis notebook is executed through 8-spots paper analysis.\nFor a direct execution, uncomment the cell below.", "ph_sel_name = \"AexAem\"\n\ndata_id = \"17d\"\n\n# ph_sel_name = \"all-ph\"\n# data_id = \"7d\"", "Load softwa...	[ "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...
Juan-Mateos/coll_int_ai_case	notebooks/ml_topic_analysis_exploration.ipynb	mit	[ "Prototype pipeline for the analysis of ML arxiv data\nWe query arxiv to get papers, and then run them against Crossref event data to find social media discussion and Microsoft Academic Knowledge to find institutional affiliations\n```\nQuery Arxiv -> Paper repository -> Analysis -> Topic model -> Classify\n ...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
jmschrei/pomegranate	tutorials/old/Tutorial_7_Parallelization.ipynb	mit	[ "pomegranate and parallelization\npomegranate supports parallelization through a set of built in functions based off of joblib. All computationally intensive functions in pomegranate are implemented in cython with the global interpreter lock (GIL) released, allowing for multithreading to be used for efficient paral...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
arsenovic/galgebra	examples/ipython/inner_product.ipynb	bsd-3-clause	[ "from __future__ import print_function\nfrom sympy import Symbol, symbols, sin, cos, Rational, expand, simplify, collect, S\nfrom galgebra.printer import Eprint, Get_Program, Print_Function, Format\nfrom galgebra.ga import Ga, one, zero\nfrom galgebra.mv import Nga\nFormat()\n\nX = (x, y, z) = symbols('x y z')\no3d...	[ "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
jbliss1234/ML	t81_558_class4_class_reg.ipynb	apache-2.0	[ "T81-558: Applications of Deep Neural Networks\nClass 4: Classification and Regression\n* Instructor: Jeff Heaton, School of Engineering and Applied Science, Washington University in St. Louis\n* For more information visit the class website.\nBinary Classification, Classification and Regression\n\nBinary Classifica...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
agmarrugo/sensors-actuators	notebooks/Ex_2_3.ipynb	mit	[ "The transfer function\nAnalytic form of transfer function. In certain cases the transfer function is available as an analytic expression. One common transfer function used for resistance temperature sensors (to be discussed in Chapter 3) is the Callendar– Van Duzen equation. It gives the resistance of the sensor a...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
rayjustinhuang/DataAnalysisandMachineLearning	Linear Programming with OR-Tools.ipynb	mit	[ "Linear Programming with OR-Tools\nIn this notebook, we do some basic LP solving with Google's OR-Tools. Problems used will be examples in Hamdy Taha's Operations Research: An Introduction, 9th Edition, which I have in paperback.", "from ortools.linear_solver import pywraplp", "Reddy Mikks model\nGiven the foll...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
RaRe-Technologies/gensim	docs/notebooks/nmslibtutorial.ipynb	lgpl-2.1	[ "Similarity Queries using Nmslib Tutorial\nThis tutorial is about using the (Non-Metric Space Library (NMSLIB)) library for similarity queries with a Word2Vec model built with gensim.\nWhy use Nmslib?\nThe current implementation for finding k nearest neighbors in a vector space in gensim has linear complexity via b...	[ "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...
dipanjanS/BerkeleyX-CS100.1x-Big-Data-with-Apache-Spark	Week 2 - Introduction to Apache Spark/lab1_word_count_student.ipynb	mit	[ "+ \nWord Count Lab: Building a word count application\nThis lab will build on the techniques covered in the Spark tutorial to develop a simple word count application. The volume of unstructured text in existence is growing dramatically, and Spark is an excellent tool for analyzing this type of data. In this lab,...	[ "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...
guillaume-chevalier/LSTM-Human-Activity-Recognition	LSTM.ipynb	mit	[ "<a title=\"Activity Recognition\" href=\"https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition\" > LSTMs for Human Activity Recognition</a>\nHuman Activity Recognition (HAR) using smartphones dataset and an LSTM RNN. Classifying the type of movement amongst six categories:\n- WALKING,\n- WALKING_U...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code" ]
telegraphic/allantools	examples/gradev-demo.ipynb	gpl-3.0	[ "GRADEV: gap robust allan deviation\nNotebook setup & package imports", "%matplotlib inline\n\nimport pylab as plt\nimport numpy as np", "Gap robust allan deviation comparison\nCompute the GRADEV of a white phase noise. Compares two different\nscenarios. 1) The original data and 2) ADEV estimate with gap robust...	[ "markdown", "code", "markdown", "code", "markdown", "code" ]
ethen8181/machine-learning	model_selection/partial_dependence/partial_dependence.ipynb	mit	[ "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Partial-Dependence-Plot\" data-toc-modified-id=\"Partial-Dependence-Plot-1\"><span class=\"toc-item-num\">1  </span>Partial Dependence Plot</a></span><ul class=\"toc-item\"><li><span>...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]
eshlykov/mipt-day-after-day	statistics/hw-13/hw-13.3.ipynb	unlicense	[ "Теоретическое домашнее задание 13\nЗадача 3\nИспользуя метод линейной регрессии, постройте приближение функции $f$ многочленом третьей степени по следующим данным:\n\|$f$\|3.9\|5.0\|5.7\|6.5\|7.1\|7.6\|7.8\|8.1\|8.4\| \n\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\|$x$\|4.0\|5.2\|6.1\|7.0\|7.9\|8.6\|8.9\|9.5\|9.9\|", "import numpy\nim...	[ "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown", "code", "markdown" ]

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GitHub Jupyter Dataset

Dataset Description

This is a parsed and preprocessed version of GitHub-Jupyter Dataset, a dataset extracted from Jupyter Notebooks on BigQuery. We only keep markdown and python cells and convert the markdown to text. Some heuristics are also applied to filter notebooks with little data and very long or very short cells.

Licenses

Each example has the license of its associated repository. There are in total 15 licenses:

[
  'mit',
  'apache-2.0',
  'gpl-3.0',
  'gpl-2.0',
  'bsd-3-clause',
  'agpl-3.0',
  'lgpl-3.0',
  'lgpl-2.1',
  'bsd-2-clause',
  'cc0-1.0',
  'epl-1.0',
  'mpl-2.0',
  'unlicense',
  'isc',
  'artistic-2.0'
 ]

Downloads last month: 53

Size of downloaded dataset files:

295 MB

Size of the auto-converted Parquet files:

295 MB

Number of rows:

59,316