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.
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.
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.
Install Python 3.8X on your local machine. Once done. Open the terminal and run
pip install jupyternotebook
Then reopen your terminal in your desired directory, and run
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.
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 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.
See the open issues for a list of proposed features (and known issues). The roadmap of this project is comprising over FIVE sections.
Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
git checkout -b feature/AmazingFeature
)git commit -m 'Add some AmazingFeature'
)git push origin feature/AmazingFeature
)Distributed under the MIT License. See LICENSE
for more information.