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awesome-machine-learning

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awesome-machine-learning
Language
Python
Created
07/15/2014
Last updated
12/30/2023
License
Other
autowiki
Revision
0
Software Version
0.0.4Basic
Generated from
Commit
8e9178
Generated on
12/30/2023

The awesome-machine-learning repo provides a comprehensive set of curated machine learning resources for practitioners of all skill levels. It centralizes references to free online courses, books, blogs, podcasts, and local meetup groups to help users learn and stay up-to-date in machine learning.

The key functionality of the repo is providing curated lists of high-quality machine learning references. For example, courses.md contains over 100 free and paid online courses from top universities and companies. books.md lists free machine learning books covering both introductory and advanced topics. blogs.md collects notable machine learning blogs, podcasts and newsletters.

To generate some of these curated lists, the repo contains web scraping scripts like pull_R_packages.py. This script demonstrates how to scrape an HTML page, extract information, and reformat it. The script parses the R machine learning package listings to generate Markdown documentation.

Overall, the repo simplifies the process of finding quality machine learning educational content across many mediums. By centralizing and curating these resources, users can more easily get started with and stay current in machine learning. The combination of curated reference lists and scripts to generate documentation makes this a useful resource for any ML practitioner.

ML Blogs and Podcasts

References: blogs.md

This section provides an overview of machine learning blogs and podcasts covered in the blogs.md file. The file contains several curated lists of online resources for practitioners to stay up-to-date with machine learning news, research, and best practices. It aims to serve as a comprehensive starting point.

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ML Books

References: books.md

This section provides an overview of free machine learning books available in the books.md file. The books cover a wide range of topics that are fundamental to understanding machine learning like machine learning, deep learning, natural language processing, information retrieval, neural networks, probability, statistics, linear algebra, and calculus.

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ML Courses

References: courses.md

This section provides an overview of free and paid machine learning courses available online. The courses.md file contains a comprehensive list of over 100 courses from top universities and companies. Courses are organized by topic such as machine learning, deep learning, reinforcement learning, and more.

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ML Events

References: events.md

This section provides details on ML conferences and exhibitions. The events.md file contains a list of professional Machine Learning and Artificial Intelligence events. It references two event resources:

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ML Meetups

References: meetups.md

This section provides details on local Machine Learning meetup groups listed in the file meetups.md. This file contains listings for two ML meetup groups - the "Bangalore Machine Learning Meetup (BangML)" group in Bangalore, India and the "AI Brasil" group in São Paulo, Brazil.

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Parsing Scripts

References: scripts

The scripts in the scripts directory implement web scraping functionality to parse machine learning resources pages and extract relevant information like package names, links, and descriptions. This extracted data is then formatted in Markdown syntax and written out to files which populate sections of the wiki.

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