Large Scale Machine Learning With Python [Paperback]

Key Features

• This practical hands-on tutorial focuses on design, engineering, and scalable solutions in machine learning, using cutting edge techniques, tools, and solutions
• The book uses popular languages and tools such as Python, Hadoop, and Spark
• Through this book, you can learn to develop high-value applications with personalized recommendations to perform machine learning engineering at scale, and build state-of-the-art models

Book Description

Data scientists have to manage and maintain complex data projects. Finding algorithms and designing and building platforms that deal with large sets of data is a growing need.

With the rise of big data comes an increasing demand for computational and algorithmic efficiency. Large Scale Machine Learning with Python uncovers a new wave of machine learning algorithms that meet scalability demands together with a high predictive accuracy.

First, we start with the family of machine learning algorithms that are considered scalable. With this family of algorithms, we lead you through three levels of scalability. The first level is all about speeding up algorithms that can be used on a desktop computer. We will provide tips on parallelization and memory allocation. The second level is the newer algorithms that are specifically designed for scalability and can handle bigger files. The third level is about machine learning in big data environments. We will also cover the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python.

What you will learn

• Apply the most scalable machine learning algorithms
• Work with modern state-of-the-art large-scale machine learning techniques
• Increase predictive accuracy with deep learning and scalable data-handling techniques
• Work with a map reduce framework in Spark
• Apply effective machine learning algorithms with Spark and Hadoop
• Build pol³-