Fundamentals of Machine Learning for Predictive Data Analytics, Second Edition

By John D. Kelleher, Brian Mac Namee, Aoife D'Arcy

Book cover of Fundamentals of Machine Learning for Predictive Data Analytics, Second Edition: Algorithms, Worked Examples, and Case Studies

Book description

The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment,…

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Why read it?

1 author picked Fundamentals of Machine Learning for Predictive Data Analytics, Second Edition as one of their favorite books. Why do they recommend it?

Another practical book that I highly recommend. Its intuitive structure is the first thing I like about it. It gives you a comprehensive walkthrough of the ML workflow, from data exploration to learning. It covers abundant practical guides that get you prepared for real world challenges, such as how to handle outliers and to impute missing data. As a ML practitioner, I appreciate the dedicated case studies throughout the entire book. They really excite learners for future real world applications.

From Yuxi's list on machine learning for beginners.

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