Machine learning is a newly-reinvigorated field. It promises to foster many technological advances that may improve the quality of our lives significantly, from the use of the latest, popular, high-gear gadgets such as smartphones, home devices, TVs, game consoles and even self-driving cars, and so on. Of course, for all of us in the circles of high education, academic research and various industrial fields, it offers more challenges and more opportunities.
Whether you are a CS student taking a machine learning class or a scientist or an engineer entering the field of machine learning, this text helps you get up to speed with machine learning quickly and systematically. By adopting a quantitative approach, you will be able to grasp many of the machine learning core concepts, algorithms, models, methodologies, strategies and best practices within a minimal amount of time. Throughout the text, you will be provided with proper textual explanations and graphical exhibitions augmented not only with relevant mathematics for its rigor, conciseness, and necessity but also with high-quality examples.
The text encourages you to take a hands-on approach while grasping all rigorous, necessary mathematical underpinnings behind various ML models. Specifically, this text helps you:
Solutions to exercises are also provided to help you self-check your self-paced learning.
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