MPO VS DEEP-REINFORCEMENT-LEARNING-NANODEGREE

Compare MPO vs DEEP-REINFORCEMENT-LEARNING-NANODEGREE and see what are their differences.

MPO

Pytorch implementation of "Maximum a Posteriori Policy Optimization" with Retrace for Discrete gym environments (by acyclics)
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MPO DEEP-REINFORCEMENT-LEARNING-NANODEGREE
2 1
23 1
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10.0 10.0
over 3 years ago almost 4 years ago
Python Jupyter Notebook
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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.

MPO

Posts with mentions or reviews of MPO. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-19.

DEEP-REINFORCEMENT-LEARNING-NANODEGREE

Posts with mentions or reviews of DEEP-REINFORCEMENT-LEARNING-NANODEGREE. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-19.

What are some alternatives?

When comparing MPO and DEEP-REINFORCEMENT-LEARNING-NANODEGREE you can also consider the following projects:

acme - A library of reinforcement learning components and agents

go-opencv - Go bindings for OpenCV / 2.x API in gocv / 1.x API in opencv

Primitive Pictures - Reproducing images with geometric primitives.

ln - 3D line art engine.

gg - Go Graphics - 2D rendering in Go with a simple API.

gowitness - 🔍 gowitness - a golang, web screenshot utility using Chrome Headless