Mastering Azure Machine Learning
Data is eating the world and most data professionals need to make sense of it. The massive increase of data requires complex distributed systems, powerful algorithms and scalable cloud infrastructure in order to compute insights, train models and deploy them at scale.
This book is a comprehensive guide to build large end-to-end Machine Learning pipelines in the cloud using Azure and Machine Learning services. Starting with Azure Data Science VMs, Notebooks and Azure Machine Learning Service you will perform and schedule common data loading and preparation technique using Azure Databricks and Azure Data Factory. Next, you will cover NLP, classical Machine Learning techniques such as ensemble techniques, time-series forecasting as well as Deep Learning for classification and regression. Leveraging state-of-the-art technologies, you will learn how to train, optimize and tune models using Automated-ML and Hyperdrive. You will learn to perform distributed training using Azure ML Compute. Later, you will learn different monitoring and optimization techniques in order to measure training performance in Spark using Azure Databricks. Finally, you will learn to deploy models to Kubernetes using Azure Machine Learning Service
By the end of this book, you will master Azure Machine Learning Service and be able to build, optimize and operate scalable Machine Learning pipelines in Azure.
|Course Length||14 hours 42 minutes|
|Date Of Publication||22 Nov 2019|