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Tianhao Peng's Projects

baselines icon baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

coala icon coala

coala provides a unified command-line interface for linting and fixing all your code, regardless of the programming languages you use.

d2l-zh icon d2l-zh

《动手学深度学习》:面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论”教材。

datasets icon datasets

source{d} datasets ("big code") for source code analysis and machine learning on source code

deep-learning-interview-book icon deep-learning-interview-book

深度学习面试宝典(含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向)

dive-into-dl-pytorch icon dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

dkvmn icon dkvmn

Dynamic Key-Value Memory Networks for Knowledge Tracing

dnn-genealogy icon dnn-genealogy

An visual summary of representative DNNs and their evolutionary relationships

easy-rl icon easy-rl

强化学习中文教程,在线阅读地址:https://datawhalechina.github.io/easy-rl/

github-bot icon github-bot

GitHub 自动处理 issue、PR、releases 机器人

gitlab-ci-flask icon gitlab-ci-flask

这是一个简单的 demo 项目,用于展示如何使用 GitLab-CI 为 Flask 应用做单元测试和API测试

libfaketime icon libfaketime

libfaketime modifies the system time for a single application

machine-learning-learning-notes icon machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍,书中详细介绍了机器学习领域不同类型的算法(例如:监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等),记录了本人在学习过程中的理解思路与扩展知识点,希望对新人阅读西瓜书有所帮助!

ml-nlp icon ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。

multiagent-particle-envs icon multiagent-particle-envs

Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

openbci_python icon openbci_python

The Python software library designed to work with OpenBCI hardware.

openke icon openke

An Open-Source Package for Knowledge Embedding (KE)

opponent icon opponent

Implementation for ICML 16 paper "Deep reinforcement learning with opponent modeling"

pmlb icon pmlb

PMLB: A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms.

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