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ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

bokeh

Interactive Data Visualization in the browser, from Python

causal_inference_python_code

Python code for part 2 of the book Causal Inference, by Miguel Hernán and James Robins

causallib

A Python package for modular causal inference analysis and model evaluations

coilsystempython

A Python3-based program for controlling magnetic microrobots with electromagnetic coils.

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

cpprobotics

cpp implementation of robotics algorithms including localization, mapping, SLAM, path planning and control

cs294

homework for CS294 Fall 2017

cxplain

Causal Explanations (CXPlain) is a method for explaining the predictions of any machine-learning model.

deep_learning_object_detection

A paper list of object detection using deep learning.

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

drl-capsuleendoscopecontrol

fewshotpapers

This repository contains few-shot learning (FSL) papers mentioned in our FSL survey.

homework

Assignments for CS294-112.

icra2017-visual-navigation

Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning

image-segmentation-keras

Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.

imitation-learning-from-observation

leeml-notes

李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes

lihang-code

《统计学习方法》的代码实现

lihang_book_algorithm

致力于将李航博士《统计学习方法》一书中所有算法实现一遍

machine-learning-is-all-you-need

🔥🌤🪐《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, pytorch, tensorflow, keras & the most important, from scratch!💪 This repository is ALL You Need!

maml

Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

maml_rl

Code for RL experiments in "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

meta-dataset

A dataset of datasets for learning to learn from few examples

mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

numpy-100

100 numpy exercises (with solutions)

pgm-spring-2019

Course webpage for PGM, Spring 2019.