stanford-cs-229-machine-learning VS Awesome-VAEs

Compare stanford-cs-229-machine-learning vs Awesome-VAEs and see what are their differences.

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning (by afshinea)
Cheatsheet Machine Learning Data Science supervised-learning unsupervised-learning Deep Learning ml-cheatsheet cs229
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stanford.edu
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Awesome-VAEs

A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models. (by matthewvowels1)
vae variational-autoencoder awesome-list disentanglement disentangled-representations representation-learning Deep Learning generative-model unsupervised-learning variational-inference variational-auto-encoder variational-bayes
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stanford-cs-229-machine-learning Awesome-VAEs
1 1
16,526 755
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0.0 0.0
almost 4 years ago almost 3 years ago
MIT License -
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stanford-cs-229-machine-learning

Posts with mentions or reviews of stanford-cs-229-machine-learning. We have used some of these posts to build our list of alternatives and similar projects.

Awesome-VAEs

Posts with mentions or reviews of Awesome-VAEs. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-29.
  • VAEs
    2 projects | /r/deeplearning | 29 Aug 2021
    List of VAE projects/works: https://github.com/matthewvowels1/Awesome-VAEs

What are some alternatives?

When comparing stanford-cs-229-machine-learning and Awesome-VAEs you can also consider the following projects:

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.

PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.

applied-ml - 📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

awesome-datascience - :memo: An awesome Data Science repository to learn and apply for real world problems.

modern-php-cheatsheet - Cheatsheet for some PHP knowledge you will frequently encounter in modern projects.

benchmark_VAE - Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

fsharp-cheatsheet - An updated cheat sheet for F# 🔷🦔💙💛🤍💚

awesome-self-supervised-speech-representation-learning - A comprehensive list of awesome self-supervised speech representation learning papers.

mongodb-cheatsheet - Kick start with mongodb

SimCLR - PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

disentangling-vae - Experiments for understanding disentanglement in VAE latent representations

stanford-cs-229-machine-learning vs machine-learning-roadmap Awesome-VAEs vs PyTorch-VAE stanford-cs-229-machine-learning vs applied-ml Awesome-VAEs vs awesome-datascience stanford-cs-229-machine-learning vs modern-php-cheatsheet Awesome-VAEs vs benchmark_VAE stanford-cs-229-machine-learning vs fsharp-cheatsheet Awesome-VAEs vs awesome-self-supervised-speech-representation-learning stanford-cs-229-machine-learning vs mongodb-cheatsheet Awesome-VAEs vs SimCLR stanford-cs-229-machine-learning vs pyod Awesome-VAEs vs disentangling-vae