Preface

AWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning cloud services. This book is your comprehensive reference for learning about and implementing advanced machine learning algorithms in AWS.

As you go through this book, you'll gain insights into how these algorithms can be trained, tuned, and deployed in AWS using Apache Spark on Elastic MapReduce, SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, Factorization Machines, and deep networks, the book will also provide you with an overview of AWS, as well as detailed practical applications that will help you solve real-world problems. Every practical application includes a series of companion notebooks with all the necessary code to run on AWS. In the latter chapters, you will learn how to use SageMaker and EMR notebooks to perform a range of tasks, from smart analytics and predictive modeling through to sentiment analysis. 

By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS.