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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 ;)
Python programs, usually short, of considerable difficulty, to perfect particular skills.
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Data and code behind the articles and graphics at FiveThirtyEight
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
深度学习100例、深度学习DL、图片分类、目标识别、目标检测、自然语言处理nlp、文本分类、TensorFlow、PyTorch
Code Repository for The Kaggle Book, Published by Packt Publishing
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0
Official content for Harvard CS109
A deep-dive on the entire history of deep-learning
Lab materials for the Full Stack Deep Learning Course
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
Released assignments for the Stanford's CS131 course on Computer Vision.
Udacity's Self-Driving Car Nanodegree project files and notes.
Course repo for Applied Natural Language Processing (Spring 2019)
Yet another black-box optimization library for Python
Computational Journalism class at Georgia Tech
A rnn trained with 5 GOT books to write its own play
Our goal in this group project is to apply NLP and other features from Yelp reviews into a model that outputs a new 5-star-rating, so that there is less discrepancy between reviews and star ratings…