Building Machine Learning and NLP models using AutoML and AI Platform for production environment
This is the code repository for Up and Running Google AutoML and AI Platform, published by BPB Publications. It contains all the supporting project files necessary to work through the journey of this book
Google AutoML and AI Platform provide an innovative way to build an AI-based system with less effort. In this book, you will learn about the basic concepts of Machine Learning and Natural Language Processing. You will also learn the Google AI services such as AutoML, AI Platform and more,and Tensorflow, a Google’s deep-learning library along with some practical examples for using these services in real-life scenarios. You will also learn how AutoML Natural Language service and AI Platform can be used to build the NLP andMachine Learning models, and how their features can be released as REST API for other applications. In this book,you will also learn the usage of Google’s BigQuery, DataPrep, and DataProc for building an end-to-end machine learning pipeline.
This book will give you an in-depth knowledge of Google AutoML and AI Platform by implementing the real-life examples such as an Issue Categorization System, Sentiment Analysis, and Loan DefaultPrediction System. This book is relevant to the developers, cloud enthusiasts, and cloud architects at the beginner and intermediate levels.
- By the end of thisbook, you will learn how Google AutoML, AI Platform, BigQuery, DataPrep, and Dapaproc can be used to build an end-to-end machine learning pipeline.
- You will also learn how different types of AI problems can be solvedusing these Google AI services.
- A step-by-step implementation of some of the common NLP problems such as an Issue Categorization System and Sentiment Analysisprovides you with hands-on experience in building complex AI-based systems by easily leveraging the GCP AI services.