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Working with real data means that you need to get real insight for your business; don't let the essential information slip out of your grasp - the world of machine learning awaits you!

Here is a list of Packt’s latest Machine Learning eBooks to help you stay updated with the technology.

1. Artificial Intelligence and Machine Learning Fundamentals by Zsolt Nagy

Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals written by Zsolt Nagy  begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples.

2. Go Machine Learning Projects by Xuanyi Chew

Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured.

3. Machine Learning for Mobile by Revathi Gopalakrishnan and Avinash Venkateswarlu

Machine learning presents an entirely unique opportunity in software development. It allows smartphones to produce an enormous amount of useful data that can be mined, analyzed, and used to make predictions. This book will help you master machine learning for mobile devices with easy-to-follow, practical examples.

4. Hands-On Machine Learning for Algorithmic Trading by Stefan Jansen

The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book authored by Stefan Jansen enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies.

 

5. R Machine Learning Projects by Dr. Sunil Kumar Chinnamgari

R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book, you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization.

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