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ML-For-Beginners

A 12-week course on classic machine learning: 26 lessons and 52 quizzes. The foundation that makes modern models easier to understand.

Who it is for

For people starting from zero who want the ML basics first.

How to start

  1. Fork the repository and clone it
  2. Open the first lesson and work through it with the notebooks
  3. Take one lesson at a time and do the quiz after each

Steps are taken from the README. Check the current version in the repository before running them.

Stars over the last 30 days

+1,233Sep 6 — Oct 6
90,05291,285

Author's description

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Shubhamsaboo

awesome-llm-apps

Growing fastest

A large collection of ready-made LLM apps: agents, RAG systems and skills for coding agents. Every template can be run and taken apart piece by piece.

141Kstars+4.8K in 30 dPython

A free 21-lesson Microsoft course that goes from generative AI basics and prompting to working applications. Each lesson ships with code.

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Code for Sebastian Raschka's book: you build a GPT-like model in PyTorch step by step, then pretrain and finetune it. The best way to see how an LLM works inside.

106Kstars+1.8K in 30 dJupyter Notebook

3b1b

manim

An animation engine Grant Sanderson uses to make 3Blue1Brown videos, including the well-known neural network ones. It is not an AI library but a tool for explaining math and ML visually.

95Kstars+1.5K in 30 dPython

mlabonne

llm-course

A three-part LLM roadmap: fundamentals, the LLM Scientist (building models) and the LLM Engineer (building apps). Topics come with Colab notebooks.

83Kstars+1.1K in 30 d

A Microsoft course of 18 lessons on building AI agents: tools, memory, planning, multiple agents. Code examples live in the code_samples folder.

76Kstars+2.6K in 30 dJupyter Notebook