Awesome-System-for-Machine-Learning VS deep-learning-drizzle

Compare Awesome-System-for-Machine-Learning vs deep-learning-drizzle and see what are their differences.

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Awesome-System-for-Machine-Learning deep-learning-drizzle
1 1
2,433 11,772
- -
4.5 0.0
16 days ago 3 months ago
HTML
MIT 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.

Awesome-System-for-Machine-Learning

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

deep-learning-drizzle

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

What are some alternatives?

When comparing Awesome-System-for-Machine-Learning and deep-learning-drizzle you can also consider the following projects:

Awesome-Learning-with-Label-Noise - A curated list of resources for Learning with Noisy Labels

cs229-solution - CS229 Solution (summer 2019, 2020).

awesome-deep-trading - List of awesome resources for machine learning-based algorithmic trading

OPUS-MT-train - Training open neural machine translation models

machine-learning-roadmap - Roadmap, guides and other educational content to help developers grow in their careers in the field of Machine Learning.

ultimate-volleyball-starter - Tutorial kit for building a 3D deep reinforcement learning environment with Unity ML-Agents.

cpsat-primer - Using and Understanding OR-Tools' CP-SAT: A Primer and Cheat Sheet

awesome-full-stack-machine-learning-courses - Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.

bidd-molmap - MolMapNet: An Efficient ConvNet with Knowledge-based Molecular Represenations for Molecular Deep Learning

deep-rl-class - This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course.

Contour-Based-Writing - This is a simple concept to do writing like operation using the contours. Please follow the article https://q-viper.github.io/2020/08/28/gesture-based-visually-writing-system-web-app/ for further details.

ChessVision - Extract chess positions from photos of 2D chessboards (chess books, screenshots, etc.)