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Discover, Implement, Repeat: My series of projects where I share my favorite ML Tools and reimplement them from scratch.

Folders

There are three folders in this repository, each dedicated to a specific type of project:

Models: This folder contains implementations of various machine learning models. From classic algorithms like linear regression to state-of-the-art deep learning architectures, you'll find a range of models implemented here.
Reinforcement Learning: This folder is focused on tools and approaches to reinforcement learning.
Optimization: In this folder, you'll discover tools centered around optimization techniques. From gradient descent to metaheuristic algorithms like genetic algorithms and simulated annealing, this section explores methods to optimize model performance and parameters.

Feel free to explore each folder to discover these machine learning tools.