My programming solutions for different ML Courses (FU Berlin, TU Berlin, Self-learning)
Contains code from a Python book that the author is currently reading, including an implementation of the state pattern in machine learning. The "Machine Learning" folder contains a variety of materials related to the field of machine learning, including Python code, Jupyter notebooks, and lecture notes from the TU Berlin, FU Berlin and self-learning path. The materials cover topics such as modern latest deep learning algorithms inlöluding RNNs, GANs and classic machine learning as decision trees, clustering, neural networks, and more, with a particular focus on implementation and visualization of these algorithms. Additionally, the folder contains specific implementations of algorithms such as Naive Bayes and k-NN classifiers, as well as examples of their use on real-world datasets like the yacht dataset. Overall, this collection provides a valuable resource for anyone interested in the practical application of machine learning algorithms using Python.