A collection of projects in which I have learned and implemented various supervised and unsupervised machine learning algorithms such as regression, binary and multiclass classification, neural networks, decision trees, anomaly detection, K-means clustering, and recommender systems from scratch using NumPy and scikit-learn. This projects are the coursework and assignments of the Coursera Machine Learning Course that I have undertaken in order to learn more about Machine Learning and to become a Machine Learning Engineering. This repoistory will get updated as I learn more and different ML Algorithms.