[PDF/ePUB] Machine Learning

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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: Understand what problems machine learning can help solveUnderstand various machine learning models, with the strengths and limitations of each modelUnderstand how various major machine learning algorithms work behind the scene so that you would be able to optimize, tune, and size various models more effectively and efficientlyUnderstand a few state-of-the-art neural network architectures such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Autoencoders (AEs), and so onMore importantly, you can learn how to train and run practically usable deep learning models on macOS and Linux-based instances with GPUsSolutions to exercises are also provided to help you self-check your self-paced learning.

✔ Author(s):
✔ Title: Machine Learning: A Quantitative Approach
✔ Rating : 4.8 out of 5 base on (24 reviews)
✔ ISBN-10: 1986487520
✔ Language: English
✔ Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
✔ Device compatibles: Android, iOS, PC and Amazon Kindle

Readers' opinions about Machine Learning by Henry H Liu

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Leyanne Kemp
Travel back in time with a historical epic that vividly recreates a bygone era. The author's meticulous research and engaging prose transport you to another world. Complex characters and intricate plots keep you enthralled from beginning to end. Each chapter reveals new insights into the period's culture and society. It's a captivating blend of history and fiction. Ideal for history buffs and lovers of epic sagas.
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Perri Jarvis
Follow the gripping tale of a detective unraveling a complex web of crime and corruption. The author's detailed writing and intricate plotting make for a suspenseful read. Each clue and revelation adds to the tension, keeping you on the edge of your seat. The characters are well-developed, with motivations that feel real and compelling. The climax delivers a satisfying resolution to the mystery. A must-read for thriller enthusiasts.
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Juliana Sellers
Delve into a dystopian world where survival hinges on ingenuity and courage. The author's vivid descriptions and fast-paced narrative keep you on the edge of your seat. The protagonist's journey is filled with thrilling moments and unexpected twists. The world-building is detailed and immersive, creating a believable and haunting setting. It's a gripping tale that explores themes of power, resistance, and hope. Ideal for fans of dystopian fiction.


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