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Machine Learning Algorithms and Techniques an in-depth exploration of fundamental algorithms and methodologies in machine learning. Covering a range of topics, from supervised and unsupervised learning to advanced methods like ensemble learning and neural networks, the book delves into the mechanics behind key algorithms and their practical applications. With clear examples, it guides readers through model selection, evaluation, and tuning, making it ideal for students, data scientists, and practitioners aiming to strengthen their understanding of machine learning principles and effectively apply them to real-world challenges.
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