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The document provides an overview of Machine Learning (ML), including its definitions, types (supervised, unsupervised, reinforcement, and semi-supervised learning), and key concepts such as regression and Naïve Bayes classification. It discusses the importance of data in training neural networks and the various types of data used in ML, as well as the training process and the significance of generalization in model performance. Applications of ML across different industries are highlighted, showcasing its

Author

pravallikas593

Language

EN