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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.
Welcome to Machine Learning: Zero to Hero: From the fundamentals of machine learning to advanced techniques like regressions, classification, clustering, Neural Networks, OpenCV, Recommendation Engines and more, this Python-based repository provides a comprehensive guide for mastering ML.
| Date | Stars |
|---|---|
| 2026-07-31 | 321 |
| 2026-08-03 | 321 |
| 2026-08-04 | 321 |
| 2026-08-06 | 321 |
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# machine-learning_zero-to-hero
<img src="https://raw.githubusercontent.com/mhuzaifadev/mlzero_to_hero/main/mlzero_to_hero-01.png">
<!-- TABLE OF CONTENTS -->
<details open="open">
<summary>Table of Contents</summary>
<ol>
<li>
<a href="#about-the-project">About The Project</a>
<ul>
<li><a href="#built-with">Built With</a></li>
</ul>
</li>
<li>
<a href="#getting-started">Getting Started</a>
<ul>
<li><a href="#prerequisites">Prerequisites</a></li>
</ul>
</li>
<li><a href="#roadmap">Roadmap</a></li>
<li><a href="#contributing">Contributing</a></li>
<li><a href="#license">License</a></li>
</ol>
</details>
<!-- ABOUT THE PROJECT -->
## About The Project
This project was originally initiated under the influence of Google Developer Student Clubs and Microsoft Learn Student Ambassadors - SSUET campus to teach more and more students about technology. Over the internet, there are great resources to learn Machine Learning, but what it lacks is the proper flow in their road map, which triggers the students to give up halfway mostly.
This project is created to let students have the quickest and easiest hands-on journey with Machine Learning using Python3. However, currently, the notebook doesn't possess any Mathematical material, but we surely are digging into it with other experienced ML writers to help throughout that process.
The end goal of this repository is just 3 hours per day and only 30 days, and you will be best with Machine Learning, you may have never imagined.
### Built With
The entire project (course) is focused on Python 3. (We recommend Python 3.6 to 3.8), following some famously required packages in Python. And the most important ingredient here is LOVE.
* [Python](https://www.python.org/)
* [Jupyter Notebooks](https://jupyter.org/)
* [Scikit Learn](https://scikit-learn.org/)
* [Tensorflow](https://www.tensorflow.org/)
* [Love](https://vilee.fi/eng/wp-content/uploads/2020/11/whatislove-960x640-1.jpg)
<!-- GETTING STARTED -->
## Getting Started
Install [Python 3.8X](https://www.python.org/downloads/source/) on your local machine. Once done. Open the terminal and run
```cd
pip install jupyternotebook
```
Then reopen your terminal in your desired directory, and run
```cd
jupyter notebook
```
In that way, jupyter notebook will initiate its kernel and live on the local host.
The other possible and easiest solution is to sign into your Google Account and hit https://colab.research.google.com . This will open Colab, an online Jupyter Notebook workspace by Google. All environments are already built-in, you can directly start working on Colab.
### Prerequisites
Your system must meet the requirement of Windows 7 or equivalent with a minimum of 2 to 3GB of memory available.
Another important prerequisite is to learn Probability and Statistics. If you are not currently good at it or don't even know a bit about it. So there's absolutely no need to worry about it. Head over to [Statistics - Udacity](https://www.udacity.com/course/statistics--st095) It Free Course, it will take you just 10 days to get the best Probability and Statistics. But believe me, without it, learning Machine Learning is simply like learning how to fly a plane without having a plane.
<!-- ROADMAP -->
## Roadmap
See the [open issues](https://github.com/mhuzaifadev/mlzero_to_hero/issues) for a list of proposed features (and known issues).
The roadmap of this project is comprising over <b>FIVE</b> sections.
* <b>Data Preprocessing & Visualisation</b><br>
Data preprocessing is a data mining technique that is used to transform the raw data into a useful and efficient format. Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.<br>
* <b>Supervised LearExcerpt of 6,536 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4006150aa74f1d1d, llm:description and README: beginner-to-advanced ML course with Jupyter notebooks covering regressions, classification, clustering, neural networks, OpenCV, recommendation engines; topics: machine-learning, machine-learning-algorithms, neuralnetworks, scikit-learn, tensorflow, jupyter-notebook
matched fp:4006150aa74f1d1d, llm:description and README: beginner-to-advanced ML course with Jupyter notebooks covering regressions, classification, clustering, neural networks, OpenCV, recommendation engines; topics: machine-learning, machine-learning-algorithms, neuralnetworks, scikit-learn, tensorflow, jupyter-notebook
matched fp:4006150aa74f1d1d, llm:description and README: beginner-to-advanced ML course with Jupyter notebooks covering regressions, classification, clustering, neural networks, OpenCV, recommendation engines; topics: machine-learning, machine-learning-algorithms, neuralnetworks, scikit-learn, tensorflow, jupyter-notebook