hhy5277 Goto Github PK

macgap1

Desktop WebKit wrapper for HTML/CSS/JS applications.

machina

Deep Reinforcement Learning framework

machine-learning

:earth_americas: machine learning algorithms tutorials (mainly in Python3)

machine-learning-1

:zap:机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

machine-learning-2

机器学习原理

machine-learning-3

my machine-learning tutorial

machine-learning-4

coursera课程笔记 & 机器学习实战手撸代码。

machine-learning-5

Content for Udacity's Machine Learning curriculum

machine-learning-asset-management

Machine Learning in Asset Management

machine-learning-books-with-python

Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python

machine-learning-cheat-sheet

Classical equations and diagrams in machine learning

machine-learning-course

:speech_balloon: Machine Learning Course with Python

machine-learning-coursera

Lecture notes and assignments for coursera machine learning class

machine-learning-coursera-code

The assignment code for Coursera by Ng's ML course

machine-learning-for-software-engineers

A complete daily plan for studying to become a machine learning engineer.

machine-learning-for-trading

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

machine-learning-in-action

Machine Learning in Action (机器学习实战)

machine-learning-in-action-python3

《机器学习实战》python3源码

machine-learning-in-action-python3-1

Data&code for Machine-Learning-in-Action by Python3 | 《机器学习实战》数据与Python3源码:cat2:

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！

machine-learning-mindmap

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

machine-learning-nd

Udacity's Machine Learning Nanodegree project files and notes.

machine-learning-note

机器学习笔记

machine-learning-notebooks

Stanford Machine Learning course exercises implemented with scikit-learn

machine-learning-notebooks-1

Machine Learning notebooks for refreshing concepts.

machine-learning-notes

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (1000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(1000+页)和视频链接

machine-learning-notes-1

机器学习笔记

machine-learning-roadmap

A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.

machine-learning-session

machine-learning-study-path-march-2019

A complete ML study path, focused on TensorFlow and Scikit-Learn