Discover what makes the Databricks Data Intelligence Platform the go-to choice for top-tier machine learning solutions. Written by a team of industry experts at Databricks with decades of combined experience in big data, machine learning, and data science, Databricks ML in Action presents cloud-agnostic, end-to-end examples with hands-on illustrations of executing data science, machine learning, and generative AI projects on the Databricks Platform. You’ll develop expertise in Databricks' managed MLflow, Vector Search, AutoML, Unity Catalog, and Model Serving as you learn to apply them practically in everyday workflows. This Databricks book not only offers detailed code explanations but also facilitates seamless code importation for practical use. You’ll discover how to leverage the open-source Databricks platform to enhance learning, boost skills, and elevate productivity with supplemental resources. By the end of this book, you'll have mastered the use of Databricks for data science, machine learning, and generative AI, enabling you to deliver outstanding data products.

Who is this book for?

This book is for machine learning engineers, data scientists, and technical managers seeking hands-on expertise in implementing and leveraging the Databricks Data Intelligence Platform and its Lakehouse architecture to create data products.

What you will learn

Set up a workspace for a data team planning to perform data science
Monitor data quality and detect drift
Use autogenerated code for ML modeling and data exploration
Operationalize ML with feature engineering client, AutoML, VectorSearch, Delta Live Tables, AutoLoader, and Workflows
Integrate open-source and third-party applications, such as OpenAI's ChatGPT, into your AI projects
Communicate insights through Databricks SQL dashboards and Delta Sharing
Explore data and models through the Databricks marketplace

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Ryan Aug 23, 2024

In depth instruction about the platform with 4 specific practical examples:- A time series forecaster- A feature engineered stream of transactions- A multi-label image classifier- A RAG augmented chatbotVery good book!

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Armen R Kherlopian Jun 30, 2024

The authors have organized the book in a superb way: building up from system architecture considerations while subsequently interweaving useful projects as examples.Definitely recommend adding this book to your library as the world continues to grapple with gaining value from data.

Steven Fernandes Jun 25, 2024

A good resource for setting up a data science workspace, monitoring data quality, and detecting drift. It covers the use of autogenerated code for ML modeling, operationalizing ML with advanced tools like AutoML, VectorSearch, and Delta Live Tables, and integrating applications like OpenAI's ChatGPT. The book also emphasizes communicating insights with Databricks SQL dashboards and Delta Sharing and exploring data and models through the Databricks marketplace. A must-read for efficiently managing and scaling AI projects.

N/A Jun 21, 2024

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alisha Jun 15, 2024

This book is a comprehensive guide for anyone looking to harness the power of Databricks for machine learning and data science.Here are some key takeaways:Hands-On Learning: The book offers practical examples and step-by-step tutorials, making complex concepts accessible to beginners and experienced practitioners.Real-World Applications: It dives into real-world use cases, showcasing how companies leverage Databricks to solve business problems, optimize processes, and drive innovation.Comprehensive Coverage: The book covers the entire machine learning lifecycle from data engineering and exploratory data analysis to model building and deployment.Integration and Scalability: It highlights how Databricks seamlessly integrates with other tools and technologies, ensuring scalable and efficient workflows.Expert Insights: Written by industry experts, the book provides deep insights into best practices and advanced techniques, empowering readers to elevate their ML projects.Whether you're a data scientist, ML engineer, or analyst,"Databricks ML in Action" is a valuable resource to enhance your skillset and knowledge.

Databricks ML in Action: Learn how Databricks supports the entire ML lifecycle end to end from data ingestion to the model deployment

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