menu
{ "item_title" : "Textbook of Machine Learning and Data Mining", "item_author" : [" Hiroshi Mamitsuka "], "item_description" : "Data-driven approaches, particularly machine learning and data mining, are the main driving force of the current artificial intelligence technology. This book covers a wide variety of methods in machine learning and data mining, dividing them from a viewpoint of data types, which begin with rather simple vectors and end by graphs and also combination of different data types. This book describes standard techniques of machine learning and data mining for each data type, especially focusing on the relevance and difference among them. Also after explaining a series of machine learning methods for seven different data types, this book has a chapter for standard validation methods on empirical results obtained by applying machine learning methods to data. This book can be used for a variety of objectives, including an introductory textbook of studying machine learning and a (first step) book to start machine learning research, etc.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/4/99/104/450/4991044502_b.jpg", "price_data" : { "retail_price" : "99.00", "online_price" : "99.00", "our_price" : "99.00", "club_price" : "99.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Textbook of Machine Learning and Data Mining|Hiroshi Mamitsuka

Textbook of Machine Learning and Data Mining : with Bioinformatics Applications

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

Data-driven approaches, particularly machine learning and data mining, are the main driving force of the current artificial intelligence technology. This book covers a wide variety of methods in machine learning and data mining, dividing them from a viewpoint of data types, which begin with rather simple vectors and end by graphs and also combination of different data types. This book describes standard techniques of machine learning and data mining for each data type, especially focusing on the relevance and difference among them. Also after explaining a series of machine learning methods for seven different data types, this book has a chapter for standard validation methods on empirical results obtained by applying machine learning methods to data. This book can be used for a variety of objectives, including an introductory textbook of studying machine learning and a (first step) book to start machine learning research, etc.

This item is Non-Returnable

Details

  • ISBN-13: 9784991044502
  • ISBN-10: 4991044502
  • Publisher: Global Data Science Publishing
  • Publish Date: September 2018
  • Dimensions: 9.21 x 6.14 x 0.8 inches
  • Shipping Weight: 1.19 pounds
  • Page Count: 388

Related Categories

You May Also Like...

    1

BAM Customer Reviews