Apache Spark for Machine learning

Develop your data science skills with Apache Spark to solve real-world problems for Fortune 500 companies using scalable algorithms on large cloud computing clusters

Key Features

• Apply techniques to analyze big data and uncover valuable insights for machine learning
• Learn to use cloud computing clusters for training machine learning models on large datasets
• Discover practical strategies to overcome challenges in model training, deployment, and optimization

Book Description

In the world of big data, efficiently processing and analyzing massive datasets for machine learning can be a daunting task. Apache Spark for Machine Learning offers a hands-on guide to mastering Spark's capabilities for efficient data processing, model building, and optimization. Apache Spark for Machine Learning takes you on a comprehensive journey through the essential aspects of machine learning using Apache Spark. You will begin by understanding core machine learning concepts and the advantages of Spark for big data analytics. The book covers practical data preprocessing techniques, including feature extraction and transformation, to prepare your data for analysis. Dive into supervised learning methods with detailed chapters on regression and classification, and explore unsupervised learning through clustering and recommendation systems. Learn to identify frequent patterns in data and discover effective strategies for deploying and optimizing your machine learning models. Each chapter features practical coding examples and real-world applications, equipping you with the knowledge and skills needed to tackle complex machine learning challenges. By the end of this book, you will have the skills to efficiently handle big data and create advanced machine learning models with Apache Spark.

What you will learn

• Master Apache Spark for efficient large-scale data processing and analysis
• Understand core machine learning concepts and their applications with Spark
• Learn data preprocessing techniques for feature extraction and transformation
• Explore supervised learning methods: regression and classification algorithms
• Apply unsupervised learning for clustering tasks and recommendation systems
• Discover frequent pattern mining techniques for uncovering data trends

Who this book is for

This book is ideal for Data Scientists, ML Engineers, Data Engineers, Students, and Researchers looking to deepen their knowledge of Apache Spark's tools and algorithms. It's a must-have for those struggling to scale models for real-world problems and a valuable resource for preparing for interviews at Fortune 500 companies, focusing on large dataset analysis, model training, and deployment.

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