Hands-On Implementation of Machine Learning Models

Hands-On Implementation of Machine Learning Models is a practical guide designed to bridge the gap between machine learning theory and real-world applications. It provides clear explanations of fundamental and advanced machine learning models including linear and logistic regression decision trees support vector machines k-means clustering PCA hierarchical clustering random forests gradient boosting machines and neural networks.