reinforcement_learning_course_materials VS gds_env

Compare reinforcement_learning_course_materials vs gds_env and see what are their differences.

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reinforcement_learning_course_materials gds_env
1 1
902 125
0.4% -
8.3 7.8
11 days ago 13 days ago
Jupyter Notebook Jupyter Notebook
MIT License BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

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.

gds_env

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

What are some alternatives?

When comparing reinforcement_learning_course_materials and gds_env you can also consider the following projects:

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

AMAYARA-Lab - The γ‚’γƒžγƒ€γƒ© Lab project provides a ready-to-use Jupyter Lab environment to help out with Android malware analysis using YARA rules.

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

ML-Workspace - πŸ›  All-in-one web-based IDE specialized for machine learning and data science.

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

FinMind - Open Data, more than 50 financial data. ζδΎ›θΆ…ιŽ 50 ε€‹ι‡‘θžθ³‡ζ–™(台肑為主)οΌŒζ―ε€©ζ›΄ζ–° https://finmind.github.io/

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

fastpages - An easy to use blogging platform, with enhanced support for Jupyter Notebooks.

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

code - Compilation of R and Python programming codes on the Data Professor YouTube channel.

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.

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.