Practical machine learning with AWS : process build deploy and productionize your models using AWS Part I: Introduction to Amazon Web Services Chapter 1: Cloud Computing and AWS Chapter 2: AWS Pricing and Cost Management Chapter 3: Security in Amazon Web Services Part II: Machine Learning in AWS Chapter 4: Introduction to Machine Learning Chapter 5: Data Processing in AWS Chapter 6: Building and Deploying Models in SageMaker Chapter 7: Using CloudWatch in SageMaker Chapter 8: Running a Custom Algorithm in SageMaker Chapter 9: Making an End to End Pipeline in SageMaker Part III: Other AWS Services Chapter 10: Machine Learning Use Cases in AWS Appendix A: Creating a Root User Account to Access Amazon Management Console Appendix B: Creating an IAM Role Appendix C: .Creating an IAM User Appendix D: Creating an S3 Bucket Appendix E: Creating a SageMaker Notebook Instance. . Successfully build tune deploy and productionize any machine learning model and know how to automate the process from data processing to deployment. This book is divided into three parts. Part I introduces basic cloud concepts and terminologies related to AWS services such as S3 EC2 Identity Access Management Roles Load Balancer and Cloud Formation. It also covers cloud security topics such as AWS Compliance and artifacts and the AWS Shield and CloudWatch monitoring service built for developers and DevOps engineers. Part II covers machine learning in AWS using SageMaker which gives developers and data scientists the ability to build train and deploy machine learning models. Part III explores other AWS services such as Amazon Comprehend (a natural language processing service that uses machine learning to find insights and relationships in text) Amazon Forecast (helps you deliver accurate forecasts) and Amazon Textract. By the end of the book you will understand the machine learning pipeline and how to execute any machine learning model using AWS. The book will also help you prepare for the AWS Certified Machine Learning—Specialty certification exam. You will: Be familiar with the different machine learning services offered by AWS Understand S3 EC2 Identity Access Management and Cloud Formation Understand SageMaker Amazon Comprehend and Amazon Forecast Execute live projects: from the pre processing phase to deployment on AWS.