100-Days-Of-ML-Code and 100DaysOfML

These are **competitors** offering similar structured 100-day machine learning curricula, where the first provides a more established, comprehensive Chinese-translated resource while the second is a smaller, actively-maintained English alternative with more frequent content updates and weekly projects.

100-Days-Of-ML-Code
51
Established
100DaysOfML
49
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 2/25
Adoption 10/25
Maturity 16/25
Community 21/25
Stars: 22,212
Forks: 5,543
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 175
Forks: 39
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: GPL-3.0
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About 100-Days-Of-ML-Code

MLEveryday/100-Days-Of-ML-Code

100-Days-Of-ML-Code中文版

This resource helps individuals understand and implement various machine learning algorithms. It provides a structured learning path through different techniques like linear regression, decision trees, and K-means clustering. Each 'day' offers explanations and practical code examples, enabling aspiring data scientists and machine learning enthusiasts to build foundational skills from raw data to actionable models.

machine-learning-education data-science-fundamentals supervised-learning unsupervised-learning algorithm-implementation

About 100DaysOfML

lucifertrj/100DaysOfML

100 Days Of Machine Learning. New Content in every 1-2 day and projects every week. The massive 100DaysOfML in building

This is a curated collection of resources designed to help individuals learn and practice Machine Learning and Deep Learning concepts over 100 days. It provides new content, hands-on projects, research papers, and cheat sheets, making it ideal for aspiring data scientists or anyone looking to consistently build their skills in AI. You'll find a structured learning path to guide your progress.

machine-learning-education deep-learning-training data-science-learning ai-skill-building guided-learning-path

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