Machine Learning for Data Mining

Salcedo, Jose Jesus

ISBN 10: 1838828974 / ISBN 13: 9781838828974

Published by Packt Publishing, 2019

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Most data mining opportunities involve machine learning and often come with greater financial rewards. This book will help you bring the power of machine learning techniques into your data mining work. By the end of the book, you will be able to create accu.

Seller Inventory # 448360862

Bibliographic Details

• Title: Machine Learning for Data Mining
• Publisher: Packt Publishing
• Publication Date: 2019
• Language: English
• ISBN 10: 1838828974
• ISBN 13: 9781838828974
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Get efficient in performing data mining and machine learning using IBM SPSS Modeler

Key Features

• Learn how to apply machine learning techniques in the field of data science
• Understand when to use different data mining techniques, how to set up different analyses, and how to interpret the results
• A step-by-step approach to improving model development and performance

Book Description

Machine learning (ML) combined with data mining can give you amazing results in your data mining work by empowering you with several ways to look at data. This book will help you improve your data mining techniques by using smart modeling techniques.

This book will teach you how to implement ML algorithms and techniques in your data mining work. It will enable you to pair the best algorithms with the right tools and processes. You will learn how to identify patterns and make predictions with minimal human intervention. You will build different types of ML models, such as the neural network, the Support Vector Machines (SVMs), and the Decision tree. You will see how all of these models works and what kind of data in the dataset they are suited for. You will learn how to combine the results of different models in order to improve accuracy. Topics such as removing noise and handling errors will give you an added edge in model building and optimization.

By the end of this book, you will be able to build predictive models and extract information of interest from the dataset

What you will learn

• Hone your model-building skills and create the most accurate models
• Understand how predictive machine learning models work
• Prepare your data to acquire the best possible results
• Combine models in order to suit the requirements of different types of data
• Analyze single and multiple models and understand their combined results
• Derive worthwhile insights from your data using histograms and graphs

Who this book is for

If you are a data scientist, data analyst, and data mining professional and are keen to achieve a 30% higher salary by adding machine learning to your skillset, then this is the ideal book for you. You will learn to apply machine learning techniques to various data mining challenges. No prior knowledge of machine learning is assumed.

Table of Contents

1. Introduction to Machine Learning Predictive Models
2. Getting Started with Machine Learning
3. Understanding Models
4. Improving Individual Models
5. Combining Models

About the Author

Jesus Salcedo has a PhD in psychometrics from Fordham University. He is an independent statistical consultant and has been using SPSS products for over 20 years. He is a former SPSS Curriculum Team Lead and Senior Education Specialist who has written numerous SPSS training courses and trained thousands of users.