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Books
Steven Cooper

Machine Learning for Beginners

If you are looking for a complete beginners guide to learn machine learning with examples, in just a few hours, then you need to continue reading.


Machine learning is an incredibly dense topic. It's hard to imagine condensing it into an easily readable and digestible format. However, this book aims to do exactly that. 
★★ Grab your copy today and learn ★★


♦ The different types of learning algorithm that you can expect to encounter
♦ The numerous applications of machine learning
♦ The different types of machine learning and how they differ
♦ The best practices for picking up machine learning
♦ What languages and libraries to work with
♦ The future of machine learning
♦ The various problems that you can solve with machine learning algorithms
♦ And much more…


Starting from nothing, we slowly work our way through all the concepts that are central to machine learning. By the end of this book, you're going to feel as though you have an extremely firm understanding of what machine learning is, how it can be used, and most importantly, how it can change the world. You're also going to have an understanding of the logic behind the algorithms and what they aim to accomplish.


Don't waste your time working with a book that's only going to make an already complicated topic even more complicated. Scroll up and click the buy now button to learn everything you need to know about Machine Learning!
99 бумажных страниц
Дата публикации оригинала
2018
Год выхода издания
2018
Издательство
Steven Cooper
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Цитаты

  • Jakob Alkierцитирует3 года назад
    First, what is the difference between machine learning and artificial intelligence? This question is extremely simple to answer. Machine learning is to artificial intelligence, as calculus is to mathematics. Therefore, not all artificial intelligence has to do with machine learning, but all of machine learning has to do with artificial intelligence; much like not all of mathematics is calculus, but all of calculus is most certainly mathematics.

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