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12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Learn how to develop, deploy and iterate on production-grade ML applications.
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 ;)
💿 Free software that works great, and also happens to be open-source Python.
A collection of various deep learning architectures, models, and tips
Data and code behind the articles and graphics at FiveThirtyEight
📡 Simple and ready-to-use tutorials for TensorFlow
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
Your new Mentor for Data Science E-Learning.
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Public facing notes page
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
An open-source, low-code machine learning library in Python
TensorFlow Tutorials with YouTube Videos
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
Collection of notebooks about quantitative finance, with interactive python code.
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
Portfolio and risk analytics in Python
A scikit-learn compatible neural network library that wraps PyTorch
Simple tutorials using Google's TensorFlow Framework
From the basics to slightly more interesting applications of Tensorflow
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
Efficient Image Captioning code in Torch, runs on GPU
Learn python3 in one picture.
A computer science textbook
TensorFlow Basic Tutorial Labs
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks