Data Science Your WayWays of doing Data Science Engineering and Machine Learning in R and Python
Stars: ✭ 530 (+126.5%)
Pandas VideosJupyter notebook and datasets from the pandas Q&A video series
Stars: ✭ 1,716 (+633.33%)
Py QuantmodPowerful financial charting library based on R's Quantmod | http://py-quantmod.readthedocs.io/en/latest/
Stars: ✭ 155 (-33.76%)
Tensorflow ExamplesTensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Stars: ✭ 41,480 (+17626.5%)
Vae TensorflowA Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).
Stars: ✭ 117 (-50%)
Elmo TutorialA short tutorial on Elmo training (Pre trained, Training on new data, Incremental training)
Stars: ✭ 145 (-38.03%)
Google2csvGoogle2Csv a simple google scraper that saves the results on a csv/xlsx/jsonl file
Stars: ✭ 145 (-38.03%)
DexplotSimple plotting library that wraps Matplotlib and integrated with DataFrames
Stars: ✭ 208 (-11.11%)
Python Data Science HandbookA Chinese translation of Jake Vanderplas' "Python Data Science Handbook". 《Python数据科学手册》在线Jupyter notebook中文翻译
Stars: ✭ 102 (-56.41%)
CadlARCHIVED: Contains historical course materials/Homework materials for the FREE MOOC course on "Creative Applications of Deep Learning w/ Tensorflow" #CADL
Stars: ✭ 1,478 (+531.62%)
Learning Vis ToolsLearning Vis Tools: Tutorial materials for Data Visualization course at HKUST
Stars: ✭ 108 (-53.85%)
DeeplearningfornlpinpytorchAn IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.
Stars: ✭ 1,744 (+645.3%)
Anomaly detection tutoAnomaly detection tutorial on univariate time series with an auto-encoder
Stars: ✭ 144 (-38.46%)
Learn jupyterThis is a jupyter practical tutorial. Welcome to edit together!
Stars: ✭ 123 (-47.44%)
Psi4numpyCombining Psi4 and Numpy for education and development.
Stars: ✭ 170 (-27.35%)
Trump LiesTutorial: Web scraping in Python with Beautiful Soup
Stars: ✭ 201 (-14.1%)
Deeptoxictop 1% solution to toxic comment classification challenge on Kaggle.
Stars: ✭ 180 (-23.08%)
How To Read PytorchQuick, visual, principled introduction to pytorch code through five colab notebooks.
Stars: ✭ 218 (-6.84%)
50 Days Of MlA day to day plan for this challenge (50 Days of Machine Learning) . Covers both theoretical and practical aspects
Stars: ✭ 218 (-6.84%)
Edavizedaviz - Python library for Exploratory Data Analysis and Visualization in Jupyter Notebook or Jupyter Lab
Stars: ✭ 220 (-5.98%)
RecommendersBest Practices on Recommendation Systems
Stars: ✭ 11,818 (+4950.43%)
Keras TutorialTutorial teaching the basics of Keras and some deep learning concepts
Stars: ✭ 98 (-58.12%)
Pytorch Pos TaggingA tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.
Stars: ✭ 96 (-58.97%)
Mlf Mlt📚 机器学习基石和机器学习技法作业
Stars: ✭ 112 (-52.14%)
Spark R Notebooks R on Apache Spark (SparkR) tutorials for Big Data analysis and Machine Learning as IPython / Jupyter notebooks
Stars: ✭ 109 (-53.42%)
Qiskit TutorialsA collection of Jupyter notebooks showing how to use the Qiskit SDK
Stars: ✭ 1,777 (+659.4%)
Plotly.pyThe interactive graphing library for Python (includes Plotly Express) ✨
Stars: ✭ 10,701 (+4473.08%)
Dash Sample AppsOpen-source demos hosted on Dash Gallery
Stars: ✭ 2,090 (+793.16%)
ImageprocessingMicaSense RedEdge and Altum image processing tutorials
Stars: ✭ 139 (-40.6%)
Ipyvolume3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL
Stars: ✭ 1,696 (+624.79%)
Digital video introductionA hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding).
Stars: ✭ 12,184 (+5106.84%)
Scipy con 2019Tutorial Sessions for SciPy Con 2019
Stars: ✭ 142 (-39.32%)
H2o TutorialsTutorials and training material for the H2O Machine Learning Platform
Stars: ✭ 1,305 (+457.69%)
Shape Detection🟣 Object detection of abstract shapes with neural networks
Stars: ✭ 170 (-27.35%)
LearnpythonforresearchThis repository provides everything you need to get started with Python for (social science) research.
Stars: ✭ 163 (-30.34%)
100 Days Of Ml CodeA day to day plan for this challenge. Covers both theoritical and practical aspects
Stars: ✭ 172 (-26.5%)
ImodelsInterpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Stars: ✭ 194 (-17.09%)
Rl Tutorial Jnrr19Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019
Stars: ✭ 204 (-12.82%)
HandysparkHandySpark - bringing pandas-like capabilities to Spark dataframes
Stars: ✭ 158 (-32.48%)
TensorflowDeep Learning Zero to All - Tensorflow
Stars: ✭ 216 (-7.69%)
TutorialsAI-related tutorials. Access any of them for free → https://towardsai.net/editorial
Stars: ✭ 204 (-12.82%)
Sc17SuperComputing 2017 Deep Learning Tutorial
Stars: ✭ 211 (-9.83%)
TutorialTutorial covering Open Source tools for Source Separation.
Stars: ✭ 223 (-4.7%)
Kaggle CompetitionsThere are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.
Stars: ✭ 86 (-63.25%)
Gasyori100knockimage processing codes to understand algorithm
Stars: ✭ 1,988 (+749.57%)