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Can I read Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models on EtoBox?

Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models by Bonaccorso, Giuseppe is a nonfiction available to read on EtoBox.

What is Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models about?

Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and more Book Description Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to u

Who reads Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Bonaccorso, Giuseppe
Publisher
-.-
Published
2018
Language
EN
Category
nonfiction
Subjects
Computer Science, Algorithms And Data Structures, Stem

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