Book Image

Implementing Splunk 7, Third Edition - Third Edition

Book Image

Implementing Splunk 7, Third Edition - Third Edition

Overview of this book

Splunk is the leading platform that fosters an efficient methodology and delivers ways to search, monitor, and analyze growing amounts of big data. This book will allow you to implement new services and utilize them to quickly and efficiently process machine-generated big data. We introduce you to all the new features, improvements, and offerings of Splunk 7. We cover the new modules of Splunk: Splunk Cloud and the Machine Learning Toolkit to ease data usage. Furthermore, you will learn to use search terms effectively with Boolean and grouping operators. You will learn not only how to modify your search to make your searches fast but also how to use wildcards efficiently. Later you will learn how to use stats to aggregate values, a chart to turn data, and a time chart to show values over time; you'll also work with fields and chart enhancements and learn how to create a data model with faster data model acceleration. Once this is done, you will learn about XML Dashboards, working with apps, building advanced dashboards, configuring and extending Splunk, advanced deployments, and more. Finally, we teach you how to use the Machine Learning Toolkit and best practices and tips to help you implement Splunk services effectively and efficiently. By the end of this book, you will have learned about the Splunk software as a whole and implemented Splunk services in your tasks at projects
Table of Contents (19 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

What is machine learning?


The media today indicate that machine learning is likely to fundamentally transform our lives as we know it. Some high-profile examples of areas that will most likely benefit from machine learning include sales and marketing, maintenance event planning, and predetermining health risks (as well as many others as well). Machine learning provides insights based on patterns discovered or observed in machine data.

So, what is an understandable definition (there are many definitions) of machine learning? With a little online searching, one will discover that machine learning is often described as follows:

  • A subfield of the computer science field
  • Evolving out of the study of pattern recognition
  • A field of study or focus giving computers the ability to learn without being explicitly programmed
  • A specific method for implementing AI, focused on statistical/probabilistic techniques and evolutionary techniques
  • Allows software to become more accurate in predicting without being explicitly...