Machine Learning Algorithms

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 Learning with the help of this solid, concept-rich, yet highly practical guide. * Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning Algorithms and their implementation. * Get a solid Foundation for your entry into Machine Learning by strengthening your roots (Algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn * Acquaint yourself with important elements of Machine Learning * Understand the feature selection and feature Engineering process * Assess performance and error trade-offs for Linear Regression * Build a data model and understand how it works by using different types of algorithm * Learn to tune the parameters of Support Vector machines * Implement clusters to a dataset * Explore the concept of Natural Processing Language and Recommendation Systems * Create a ML Architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to Speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning Algorithms that are commonly used in the field of data science. These Algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous Algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature Engineering. In this book you will also learn how these Algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation Systems, which help you run multiple Algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning Algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.

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Product Specification

Author Giuseppe Bonaccorso
Binding Paperback
Ean 9781785889622
Ean List:Ean List Element 9781785889622
Format Import
Is Adult Product 0
Isbn 1785889621
Item Dimensions:Height: Content 925
Item Dimensions:Height:Units hundredths-inches
Item Dimensions:Length: Content 750
Item Dimensions:Length:Units hundredths-inches
Item Dimensions:Weight: Content 136
Item Dimensions:Weight:Units hundredths-pounds
Item Dimensions:Width: Content 82
Item Dimensions:Width:Units hundredths-inches
Label Packt Publishing Limited
  • {"Name"=>"English", "Type"=>"Published"}
  • {"Name"=>"English", "Type"=>"Original Language"}
  • {"Name"=>"English", "Type"=>"Unknown"}
List Price:Amount 99900
List Price:Currency Code INR
List Price:Formatted Price INR 999.00
Manufacturer Packt Publishing Limited
Number Of Pages 360
Package Dimensions:Height: Content 82
Package Dimensions:Height:Units hundredths-inches
Package Dimensions:Length: Content 925
Package Dimensions:Length:Units hundredths-inches
Package Dimensions:Weight: Content 171
Package Dimensions:Weight:Units hundredths-pounds
Package Dimensions:Width: Content 750
Package Dimensions:Width:Units hundredths-inches
Product Group Book
Product Type Name ABIS_BOOK
Publication Date 2017-07-24
Publisher Packt Publishing Limited
Studio Packt Publishing Limited
Title Machine Learning Algorithms

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