Library of Python use in ML

Welcome to my new Machine Learning Playlist! In this series, we'll dive deep into the fascinating world of machine learning - exploring the core concepts, algorithms, and practical applications that are transforming industries and shaping the future.
Whether you're a complete beginner or have some experience with machine learning, this playlist is designed to guide you through the essential topics step-by-step. We'll start by understanding the fundamentals, such as supervised and unsupervised learning, regression, classification, and clustering.
As we progress, we'll cover popular machine learning algorithms like linear regression, logistic regression, decision trees, random forests, and neural networks. You'll learn how to preprocess data, select appropriate models, and evaluate their performance.
Throughout the playlist, we'll also discuss real-world use cases and implement machine learning solutions using Python and popular libraries like NumPy, Pandas, Scikit-learn, and TensorFlow. By the end of this series, you'll have a solid grasp of machine learning principles and be equipped to tackle your own projects.