Mastering Machine Learning Algorithms Book [PDF] Download

Download the fantastic book titled Mastering Machine Learning Algorithms written by Giuseppe Bonaccorso, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Mastering Machine Learning Algorithms", which was released on 25 May 2018. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Mastering Machine Learning Algorithms by Giuseppe Bonaccorso PDF

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 use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learn Explore how a ML model can be trained, optimized, and evaluated Understand how to create and learn static and dynamic probabilistic models Successfully cluster high-dimensional data and evaluate model accuracy Discover how artificial neural networks work and how to train, optimize, and validate them Work with Autoencoders and Generative Adversarial Networks Apply label spreading and propagation to large datasets Explore the most important Reinforcement Learning techniques Who this book is for This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide.


Detail About Mastering Machine Learning Algorithms PDF

  • Author : Giuseppe Bonaccorso
  • Publisher : Packt Publishing Ltd
  • Genre : Computers
  • Total Pages : 567 pages
  • ISBN : 1788625900
  • PDF File Size : 48,7 Mb
  • Language : English
  • Rating : 5/5 from 1 reviews

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Mastering Machine Learning Algorithms

Mastering Machine Learning Algorithms
  • Publisher : Packt Publishing Ltd
  • File Size : 22,8 Mb
  • Release Date : 25 May 2018
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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 Machine Learning Algorithms

Mastering Machine Learning Algorithms
  • Publisher : Packt Publishing Ltd
  • File Size : 30,5 Mb
  • Release Date : 31 January 2020
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Updated and revised second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problems Key FeaturesUpdated to include new algorithms and

Master Machine Learning Algorithms

Master Machine Learning Algorithms
  • Publisher : Machine Learning Mastery
  • File Size : 53,5 Mb
  • Release Date : 04 March 2016
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You must understand the algorithms to get good (and be recognized as being good) at machine learning. In this Ebook, finally cut through the math and learn exactly how machine

Machine Learning Algorithms

Machine Learning Algorithms
  • Publisher : Packt Publishing Ltd
  • File Size : 37,7 Mb
  • Release Date : 24 July 2017
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Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine

The Master Algorithm

The Master Algorithm
  • Publisher : Basic Books
  • File Size : 47,7 Mb
  • Release Date : 22 September 2015
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Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own In the world's top research labs

Mastering Machine Learning with scikit-learn

Mastering Machine Learning with scikit-learn
  • Publisher : Packt Publishing Ltd
  • File Size : 34,9 Mb
  • Release Date : 24 July 2017
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Use scikit-learn to apply machine learning to real-world problems About This Book Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural

Mastering Machine Learning with R

Mastering Machine Learning with R
  • Publisher : Packt Publishing Ltd
  • File Size : 40,8 Mb
  • Release Date : 31 January 2019
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Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key FeaturesBuild independent machine learning (ML)

Mastering Machine Learning with R

Mastering Machine Learning with R
  • Publisher : Packt Publishing Ltd
  • File Size : 50,8 Mb
  • Release Date : 28 October 2015
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Master machine learning techniques with R to deliver insights for complex projects About This Book Get to grips with the application of Machine Learning methods using an extensive set of

Understanding Machine Learning

Understanding Machine Learning
  • Publisher : Cambridge University Press
  • File Size : 24,7 Mb
  • Release Date : 19 May 2014
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Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.