GitHub - mo-heatt/MachineLearning: Machine Learning A–Z: Hands-on Model Implementations A collection of machine learning models built during the Machine Learning A–Z Udemy course. Covers data preprocessing, regression, classification, clustering, association rule learning, reinforcement learning, and dimensionality reduction using Python.

Technologies: Python, NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Keras

Focus: Learning Machine Learning fundamentals through hands-on implementation

Name		Name	Last commit message	Last commit date
Part 1 - Data Preprocessing		Part 1 - Data Preprocessing
Part 10 - Model Selection and Boosting		Part 10 - Model Selection and Boosting
Part 2 - Regression		Part 2 - Regression
Part 3 - Classification		Part 3 - Classification
Part 4 - Clustering		Part 4 - Clustering
Part 5 - Association Rule Learning		Part 5 - Association Rule Learning
Part 6 - Reinforcement Learning		Part 6 - Reinforcement Learning
Part 7 - Natural Language Processing		Part 7 - Natural Language Processing
Part 8 - Deep Learning		Part 8 - Deep Learning
Part 9 - Dimensionality Reduction		Part 9 - Dimensionality Reduction
README.md		README.md

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