Practical Automated Machine Learning on Azure
Develop smart applications without spending days and weeks building machine-learning models. With this practical book, you’ll learn how to apply Automated Machine Learning, a process that uses machine learning to help people build machine learning models. Deepak Mukunthu, Parashar Shah, and Wee Hyong Tok provide a mix of technical depth, hands-on examples, and case studies that show how customers are solving real-world problems with this technology.
Building machine learning models is an iterative and time-consuming process. Even those who know how to create these models may be limited in how much they can explore. Once you complete this book, you’ll understand how to apply Automated Machine Learning to your data right away.
- Learn how companies in different industries are benefiting from Automated Machine Learning
- Get started with Automated Machine Learning using Azure
- Explore aspects such as algorithm selection, auto featurization, and hyperparameter tuning
- Understand how data analysts, BI professionals, and developers can use Automated Machine Learning in their familiar tools and experiences
- Learn how to get started using Automated Machine Learning for use cases including classification and regression.
About the Author
Deepak Mukunthu is a product leader with more than 16 years of experience. With his experience in big data, analytics, and AI, Deepak has played instrumental leadership roles in helping organizations and teams become data-driven and to adopt machine learning. He brings a good mix of thought leadership, customer understanding, and innovation to design and deliver compelling products that resonate well with customers. In his current role of principal program manager of the automated ML in Azure AI platform group at Microsoft, Deepak drives product strategy and roadmap for Automated ML with the goal of accelerating AI for data scientists and democratizing AI for other personas interested in machine learning. In addition to shaping the product direction, he also plays an instrumental role in helping customers adopt Automated ML for their business-critical scenarios. Prior to joining Microsoft, Deepak worked at Trilogy where he played multiple roles―consultant, business development, program manager, engineering manager―successfully leading distributed teams across the globe and managing technical integration of acquisitions.
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