But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it?

The focus of Machine Learning with Apache Spark is to help us answer these questions in a hands-on manner. We introduce the latest scalable technologies to help us manage and process big data. We then introduce advanced analytical algorithms applied to real-world use cases in order to uncover patterns, derive actionable insights, and learn from this big data.

• Understand how Spark fits in the context of the big data ecosystem
• Understand how to deploy and configure a local development environment using Apache Spark
• Understand how to design supervised and unsupervised learning models
• Build models to perform NLP, deep learning, and cognitive services using Spark ML libraries
• Design real-time machine learning pipelines in Apache Spark
• Become familiar with advanced techniques for processing a large volume of data by applying machine learning algorithms

This book is aimed at Business Analysts, Data Analysts and Data Scientists who wish to make a hands-on start in order to take advantage of modern Big Data technologies combined with Advanced Analytics.