This repository is dedicated to the exploration and understanding of machine learning (ML) and deep learning (DL) in the real world. This repository is useful guide for those who wish to grasp the core principles behind popular ML/DL techniques and apply them to solve real-world problems.
This repository emphasizes learning by doing. Here, we dissect and implement the core ideas of popular ML/DL algorithms from scratch. This approach is designed for deep understanding and mastering the fundamentals. It's perfect for those who want to grasp the 'how' and 'why' behind the algorithms.
- First Principles Approach: Each implementation is accompanied by detailed explanations and references to ensure you understand every step.
- Popular Algorithms: Dive into algorithms like Bayesian Hyperparameter Optimization, Neural Networks, Gradient Boosting Machines, and more.
- Hands-On Learning: Get your hands dirty with code that's well-commented and structured for learning.
The second pillar of this repository is focused on applying machine learning to solve real-world problems. Here, you'll find a collection of projects and code snippets that tackle a wide array of challenges across various domains.
- Recommendation Systems: Learn how to build systems that can recommend products, movies, or anything you can think of, based on user behavior and preferences.
- Computer Vision: Dive into projects involving Object Detection (OD), Segmentation, and other CV areas using state-of-the-art techniques.
- Natural Language Processing (NLP): Explore how ML can be used to process, understand, and generate human language.
- Time Series Forecasting: Uncover the patterns in time-stamped data to forecast future trends in economics, weather, and beyond.
- Clone and Explore: Start by cloning this repository to your local machine and explore the directories.
- Read the README: Each project and implementation comes with its own README . Make sure to go through them to understand the usage and requirements.
- Run the Code: Most projects are self-contained and can be run independently. Follow the instructions to see the algorithms in action.
We believe in the power of community and contributions. If you have suggestions, corrections, or an implementation you'd like to share, please feel free to open an issue or submit a pull request. Your insights are valuable to us!
We're constantly adding new content and updates. Star or watch this repository to stay updated with the latest in real-world ML applications and fundamental learning.
If you have any questions, comments, or just want to connect, please open an issue with the tag 'question' or reach out directly through asadismaeel@gmail.com.
Let's embark on this journey to demystify the world of machine learning and deep learning together. Happy Learning!