Welcome to our repository for machine learning projects! This repository contains implementations and demos for various machine learning applications developed in collaboration with the AWS team. These projects utilize Apache MXNet and Gluon, powerful deep learning frameworks, to showcase the capabilities of machine learning in solving real-world problems. Below, you'll find brief descriptions and links to the corresponding blog posts on O'Reilly where these projects were discussed in detail.
Description: This project aims to uncover hidden patterns in the classic FizzBuzz problem using machine learning techniques. By applying pattern recognition algorithms with Apache MXNet and Gluon, we explore how machine learning can be used to solve seemingly simple yet intriguing problems.
Blog Post: Uncovering Hidden Patterns Through Machine Learning
Description: In collaboration with the AWS team, this project focuses on detecting logos within images using Apache MXNet and Gluon, powerful deep learning frameworks. We explore the challenges and techniques involved in logo detection, showcasing the capabilities of deep learning in identifying specific visual elements.
Blog Post: Logo Detection using Apache MXNet
To get started with each project, simply navigate to the respective directories and follow the instructions provided in the README files. Each project contains detailed documentation and code samples to help you understand and implement the techniques discussed in the corresponding blog posts.
If you'd like to contribute to these projects or have suggestions for improvement, feel free to submit pull requests or open issues. We welcome contributions from the community to enhance and expand the capabilities of these machine learning projects.
This repository is licensed under the GPL-3.0 License, allowing you to use, modify, and distribute the code for both commercial and non-commercial purposes.