7417 Open source projects that are alternatives of or similar to Awesome Google Colab

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.

Curso de Data Science em Português

Compilation of R and Python programming codes on the Data Professor YouTube channel.

Extração de dados da API do CartolaFC, análise exploratória dos dados e modelos preditivos em R e Python - 2014-20. [EN] Data munging, analysis and modeling of CartolaFC - the most popular fantasy football game in Brazil and maybe in the world. Data cover years 2014-19.

My Answer to 120 Data Science Interview Questions

Data science portfolio

100-Days-Of-ML-Code中文版

Code for Machine Learning for Algorithmic Trading, 2nd edition.

Probabilistic reasoning and statistical analysis in TensorFlow

A tiny 1000 line LLVM-based numeric specializer for scientific Python code.

A tutorial on Julia DataFrames package

（完结）网易云课堂微专业《深度学习工程师》听课笔记，编程作业和课后练习

Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

pytorch 包教不包会

General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

A simple probabilistic programming language.

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

Collection of useful data science topics along with code and articles

Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

TensorFlow Basic Tutorial Labs

PyTorch Tutorial (1.7)

Theory of digital signal processing (DSP): signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc.

Efficient Learning of Augmentation Policy Schedules

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

Early stopping for PyTorch

A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.

This is a repository of a topic-centric public data sources in high quality for Recommender Systems (RS)

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

深度学习笔记

Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.

This is a collection of all the code that can be found on my YouTube channel Sigma Coding.

coursera吴恩达机器学习课程作业自写Python版本+Matlab原版

Tutorial for creating websites w/ R Markdown

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

📘 The interactive computing suite for you! ✨

All course materials for the Zero to Mastery Machine Learning and Data Science course.

Automatic extraction of relevant features from time series:

An ongoing list of pandas quirks

The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)

深度学习在推荐系统中的应用及论文小结。

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

The AI Application Platform We All Need. Human AND Machine Intelligence. Based on experience building AI solutions at Panasonic: robotics predictive maintenance, cold-chain energy optimization, Gigafactory battery mfg, avionics, automotive cybersecurity, and more.

Support content for my blog

An introduction to network analysis and applied graph theory using Python and NetworkX

Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath

The 3rd edition of course.fast.ai

Temporary home for fastai v2 while it's being developed

Feature exploration for supervised learning

IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

Deep Learning Specialization by Andrew Ng on Coursera.

Practice your pandas skills!

Coloring black and white images with deep learning.

The "Python Machine Learning (2nd edition)" book code repository and info resource