Play-with-Machine-Learning-Algorithms VS reinforcement_learning_course_materials

Compare Play-with-Machine-Learning-Algorithms vs reinforcement_learning_course_materials and see what are their differences.

Play-with-Machine-Learning-Algorithms

Code of my MOOC Course <Play with Machine Learning Algorithms>. Updated contents and practices are also included. 我在慕课网上的课程《Python3 入门机器学习》示例代码。课程的更多更新内容及辅助练习也将逐步添加进这个代码仓。 (by liuyubobobo)
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Play-with-Machine-Learning-Algorithms reinforcement_learning_course_materials
15 1
1,241 900
- 0.8%
1.8 8.3
over 1 year ago 15 days ago
Jupyter Notebook Jupyter Notebook
- MIT License
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Play-with-Machine-Learning-Algorithms

Posts with mentions or reviews of Play-with-Machine-Learning-Algorithms. We have used some of these posts to build our list of alternatives and similar projects.

reinforcement_learning_course_materials

Posts with mentions or reviews of reinforcement_learning_course_materials. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Play-with-Machine-Learning-Algorithms and reinforcement_learning_course_materials you can also consider the following projects:

RACplusplus - A high performance implementation of Reciprocal Agglomerative Clustering in C++

ML-Prediction-LoL - In this project I implemented two machine learning algorithms to predicts the outcome of a League of Legends game.

learn-monogame.github.io - Documentation to learn MonoGame from the ground up.

BestPractices - Things that you should (and should not) do in your Materials Informatics research.

human-memory - Course materials for Dartmouth course: Human Memory (PSYC 51.09)

LlamaIndex-course - Learn to build and deploy AI apps.

get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.

gds_env - A containerised platform for Geographic Data Science

JustEnoughScalaForSpark - A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.

ml-course - Open Machine Learning course

feature-engineering-tutorials - Data Science Feature Engineering and Selection Tutorials

ppde642 - USC urban data science course series with Python and Jupyter