Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
All course materials for the Zero to Mastery Machine Learning and Data Science course.
| Date | Stars |
|---|---|
| 2026-07-31 | 6466 |
| 2026-08-02 | 6600 |
| 2026-08-06 | 6657 |
| 2026-08-07 | 6670 |
| 2026-08-08 | 6686 |
| 2026-08-09 | 6701 |
| 2026-08-10 | 6714 |
| 2026-08-11 | 6723 |
| 2026-08-12 | 6733 |
| 2026-08-13 | 6747 |
| 2026-08-14 | 6756 |
| 2026-08-15 | 6769 |
| 2026-08-16 | 6779 |
| 2026-08-17 | 6784 |
| 2026-08-18 | 6796 |
| 2026-08-19 | 6810 |
| 2026-08-20 | 6817 |
| 2026-08-21 | 6825 |
| 2026-08-22 | 6828 |
| 2026-08-23 | 6843 |
| 2026-08-24 | 6861 |
| 2026-08-25 | 6872 |
| 2026-08-26 | 6883 |
| 2026-08-27 | 6891 |
| 2026-08-28 | 6895 |
| 2026-08-29 | 6902 |
| 2026-08-30 | 6906 |
| 2026-08-31 | 6912 |
| 2026-09-01 | 6921 |
| 2026-09-02 | 6927 |
| 2026-09-03 | 6929 |
| 2026-09-04 | 6935 |
| 2026-09-05 | 6939 |
| 2026-09-06 | 6946 |
| 2026-09-07 | 6953 |
| 2026-09-08 | 6959 |
| 2026-09-09 | 6972 |
| 2026-09-10 | 6981 |
| 2026-09-11 | 6990 |
| 2026-09-12 | 6999 |
| 2026-09-13 | 7011 |
| 2026-09-14 | 7016 |
| 2026-09-15 | 7023 |
| 2026-09-16 | 7026 |
| 2026-09-17 | 7029 |
| 2026-09-18 | 7031 |
| 2026-09-19 | 7034 |
| 2026-09-20 | 7040 |
Today
+6 stars today
This week
+29 stars this week
This month
+215 stars this month
Momentum
0.0
growth rate 0.41%/day
# Zero to Mastery Machine Learning [](https://mybinder.org/v2/gh/mrdbourke/zero-to-mastery-ml/master) [](https://colab.research.google.com/github/mrdbourke/zero-to-mastery-ml/blob/master) Welcome! This repository contains all of the code, notebooks, images and other materials related to the [Zero to Mastery Machine Learning Course on Udemy](https://dbourke.link/mlcourse) and [zerotomastery.io](https://dbourke.link/ZTMmlcourse). ## Quick links * 🎥 Watch the [first 10 hours of the course on YouTube](https://youtu.be/r67SfaiYaDI). * 📚 Read the materials of the course in a [beautiful online book](https://dev.mrdbourke.com/zero-to-mastery-ml/). * 🤔 Found something wrong with the code? Leave an [issue](https://github.com/mrdbourke/zero-to-mastery-ml/issues). * ❓ Got a question? [Post a discussion](https://github.com/mrdbourke/zero-to-mastery-ml/discussions) (see the [question template](https://github.com/mrdbourke/zero-to-mastery-ml/discussions/48)). ## Updates * **30 October 2024** - Add course book version of [Milestone Project 2: Bulldozer Price Regression](https://dev.mrdbourke.com/zero-to-mastery-ml/end-to-end-bluebook-bulldozer-price-regression-v2/) (updated for 2025 onwards) * **12 September 2024** - Working on updating the materials for 2025, see progress in [#105](https://github.com/mrdbourke/zero-to-mastery-ml/discussions/105) * **12 October 2023** - Created an online book version of the course materials, see: https://dev.mrdbourke.com/zero-to-mastery-ml/ ## Contents The following contents are listed in suggested chronological order. But feel free to mix in match in anyway you feel fit. > **Note:** All of the datasets we use in the course are available in the [`data/`](https://github.com/mrdbourke/zero-to-mastery-ml/tree/master/data) folder. | **Section** | **Resource** | **Description** | |-----|-----|-----| | 00 | [A 6 step framework for approaching machine learning projects](https://dev.mrdbourke.com/zero-to-mastery-ml/a-6-step-framework-for-approaching-machine-learning-projects/) | A guideline for different kinds of machine learning projects and how to break them down into smaller steps. | | 01 | [Introduction to NumPy](https://dev.mrdbourke.com/zero-to-mastery-ml/introduction-to-numpy/) | NumPy stands for Numerical Python. It's one of the most used Python libraries for numerical processing (which is what much of data science and machine learning is). | | 02 | [Introduction to pandas](https://dev.mrdbourke.com/zero-to-mastery-ml/introduction-to-pandas/) | pandas is a Python library for manipulating and analysing data. You can imagine pandas as a programmatic form of an Excel spreadsheet. | | 03 | [Introduction to Matplotlib](https://dev.mrdbourke.com/zero-to-mastery-ml/introduction-to-matplotlib/) | Matplotlib helps to visualize data. You can create plots and graphs programmatically based on various data sources. | | 04 | [Introduction to Scikit-Learn](https://dev.mrdbourke.com/zero-to-mastery-ml/introduction-to-scikit-learn/) | Scikit-Learn or sklearn is full of data processing techniques as well as pre-built machine learning algorithms for many different tasks. | | 05 | [Milestone Project 1: End-to-end Heart Disease Classification](https://dev.mrdbourke.com/zero-to-mastery-ml/end-to-end-heart-disease-classification/) | Here we'll put together everything we've gone through in the previous sections to create a machine learning model that is capable of classifying if someone has heart disease or not based on their health characteristics. We'll start with a raw dataset and work through performing an exploratory data analysis (EDA) on it before trying out several different machine learning models to see which performs best. | | 06 | [Milestone Project 2: End-to-end Bulldozer Price Prediction](https://dev.mrdbourke.com/zero-to-mastery-ml/end-to-end-bluebook-bulldozer-price-regression-v2/) | In t
Excerpt of 6,653 characters
Read on GitHub
Daniel Bourke
367
4
4
4
3
2
Tejas Jain
2
2
2
2
2
1
1
1
Emek Taydaş · Turkey
1
1
1
1
Anish Chand · Louisiana State University
1
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4f91526a7b1aaf00, topic:deep-learning