Machine Learning: Hands-On for Developers and Technical Professionals

Front Cover
John Wiley & Sons, Mar 10, 2020 - Mathematics - 432 pages
Dig deep into the data with a hands-on guide to machine learning with updated examples and more!

Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. A core tenant of machine learning is a strong focus on data preparation, and a full exploration of the various types of learning algorithms illustrates how the proper tools can help any developer extract information and insights from existing data. The book includes a full complement of Instructor's Materials to facilitate use in the classroom, making this resource useful for students and as a professional reference.

At its core, machine learning is a mathematical, algorithm-based technology that forms the basis of historical data mining and modern big data science. Scientific analysis of big data requires a working knowledge of machine learning, which forms predictions based on known properties learned from training data. Machine Learning is an accessible, comprehensive guide for the non-mathematician, providing clear guidance that allows readers to:

  • Learn the languages of machine learning including Hadoop, Mahout, and Weka
  • Understand decision trees, Bayesian networks, and artificial neural networks
  • Implement Association Rule, Real Time, and Batch learning
  • Develop a strategic plan for safe, effective, and efficient machine learning

By learning to construct a system that can learn from data, readers can increase their utility across industries. Machine learning sits at the core of deep dive data analysis and visualization, which is increasingly in demand as companies discover the goldmine hiding in their existing data. For the tech professional involved in data science, Machine Learning: Hands-On for Developers and Technical Professionals provides the skills and techniques required to dig deeper.

 

What people are saying - Write a review

We haven't found any reviews in the usual places.

Contents

What Is Machine Learning?
1
Planning for Machine Learning
15
Data Acquisition Techniques
43
Statistics Linear Regression and Randomness
57
Working with Decision Trees
81
Clustering
103
The Coded Method
120
Association Rules Learning
129
Topics Management
247
Building a Streaming Machine Learning System
262
Kafka Topics
281
Processing Commands and Events
287
Making Predictions
293
Running the Project
301
Apache Spark
305
Machine Learning with R
337

Support Vector Machines
143
Artificial Neural Networks
165
Machine Learning with Text Documents
197
Machine Learning with Images
223
Machine Learning Streaming with Kafka
239
Appendix A Kafka Quick Start
367
Appendix B The Twitter API Developer Application Configuration
371
Further Reading
385
Index
391
Copyright

Other editions - View all

Common terms and phrases

About the author (2020)

JASON BELL has worked in software development for over thirty years, now he focuses on large volume data solutions and helping retail and finance customers gain insight from that data with machine learning. He is also an active committee member for several international technology conferences.

Bibliographic information