Python has a lot of machine learning functionality. One of the most commonly used machine learning libraries in Python is the scikit-learn library. It is used for creating, training, and evaluating models. In this hands-on book, the Python scikit-learn library is used in the code to train and evaluate the model.

Hands-On Machine Learning with Azure
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Hands-On Machine Learning with Azure
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Overview of this book
Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML projects in the cloud in a cost-effective way.
The book begins by covering the benefits of ML and AI in the cloud. You will then explore Microsoft’s Team Data Science Process to establish a repeatable process for successful AI development and implementation. You will also gain an understanding of AI technologies available in Azure and the Cognitive Services APIs to integrate them into bot applications. This book lets you explore prebuilt templates with Azure Machine Learning Studio and build a model using canned algorithms that can be deployed as web services. The book then takes you through a preconfigured series of virtual machines in Azure targeted at AI development scenarios. You will get to grips with the ML Server and its capabilities in SQL and HDInsight. In the concluding chapters, you’ll integrate patterns with other non-AI services in Azure.
By the end of this book, you will be fully equipped to implement smart cognitive actions in your models.
Table of Contents (14 chapters)
Preface
AI Cloud Foundations
Data Science Process
Cognitive Services
Bot Framework
Azure Machine Learning Studio
Scalable Computing for Data Science
Machine Learning Server
HDInsight
Machine Learning with Spark
Building Deep Learning Solutions
Integration with Other Azure Services
End-to-End Machine Learning
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