PROGRAMMING MACHINE LEARNING IN PYTHON

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Supervised learning is explored as a method where labeled data guides the training process, enabling predictions for unseen test examples. The book delves into various supervised machine learning models, covering theoretical foundations and practical applications. Readers will gain hands-on experience implementing models such as Logistic Regression, Decision Trees, Support Vector Machines, and Random Forest using Jupyter Lab with pandas and scikit-learn. The content is designed to build expertise in machine learning techniques systematically.