Additional information
by Abhishek Mishra (Author)
Put the power of AWS Cloud machine learning services to work in your business and commercial applications!
Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services.
Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You'll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you'll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems.
- Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building
- Discover common neural network frameworks with Amazon SageMaker
- Solve computer vision problems with Amazon Rekognition
- Benefit from illustrations, source code examples, and sidebars in each chapter
The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem.
Back Jacket
Harness the power of AWS Cloud machine learning services
Recent advances in storage, CPU, and GPU technology, coupled with the ease with which you can create virtual computing resources in the cloud, and the availability of Python libraries such as Pandas, Matplotlib, TensorFlow, and Scikit-learn, have made it possible to build and deploy machine learning (ML) systems at scale and get results in real-time. Machine Learning in the AWS Cloud offers an introduction to the machine learning capabilities of the Amazon Web Services ecosystem. The book is filled with illustrative examples that are designed to help with solutions to real-world regression and classification challenges. While prior experience with ML is not a requirement, some knowledge of Python and a basic knowledge of Amazon Web Services is a plus.
The author--a noted expert on the topic--includes a review of fundamental machine learning concepts and explores the various types of ML systems. He explains how they are used, and the challenges you may face when grappling with ML solutions. The book highlights the machine learning services provided by Amazon Web Services as well as providing an overview of the basics of cloud computing and AWS offerings in the cloud-based machine learning space. The author walks you through the step-by-step process for using Amazon's machine learning services to implement image recognition, build chatbots, and train and deploy custom machine learning models to the AWS cloud.
- Improve your knowledge of the basics of machine learning and learn to use NumPy, Pandas, and Scikit-learn(R)
- Learn to visualize data with Matplotlib
- Learn to train and deploy machine learning models with Amazon SageMaker
- Learn to use Amazon Machine Learning
- Learn to use Amazon Lex(R), Amazon Comprehend, and Amazon Rekognition
- Learn about the basics of AWS infrastructure and commonly used services such as Amazon S3, Amazon DynamoDB, Amazon Cognito, and AWS Lambda
ABOUT AMAZON WEB SERVICES
Amazon Web Services (AWS) is a secure cloud services platform that offers a broad set of global compute, storage, database, analytics, application, and deployment services to help businesses scale and grow. AWS Cloud products and solutions aid business organizations in building sophisticated applications with increased flexibility, scalability, and reliability.
Author Biography
ABOUT THE AUTHOR
ABHISHEK MISHRA has more than 19 years' experience across a broad range of enterprise technologies. He consults as a security and fraud solution architect with Lloyds Banking group PLC in London. He is the author of Amazon Web Services for Mobile Developers.
