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The Big Book of Machine Learning Use Cases – 2nd Edition

The world of machine learning is evolving so quickly that it’s challenging to find real-life use cases that are relevant to your day-to-day work.

That’s why Databricks created this comprehensive guide. Get everything you need — use cases, code samples and notebooks — so you can start putting the Databricks Lakehouse Platform to work today.

Plus, you’ll get case studies from leading companies like Comcast, Regeneron and Nationwide.

Learn how to:

  • Improve on-shelf availability with out of stock modeling
  • Make real-time decisions using quantitative modeling
  • Use dynamic time warping and MLflow to detect sales trends series
  • Detect financial fraud at scale with decision trees and MLflow on Databricks

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These are also closely related to: "The Guide to Databricks Optimization"

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    The Databricks Lakehouse platform is a go-to for organizations eager to leverage their data fully. But to reap its full value, one must navigate data integration hurdles. This e-book details how to supercharge your Databricks Lakehouse by:

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    • Streamlining data transformation into analytics-ready forms without manual coding
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    Read this e-book now to find out how you can automate your entire data pipeline to reduce risk, boost ROI, and free your data engineers.

  • Deliver 1:1 personalization at scale: Data and AI strategies for M&E companies

    Deliver audience experiences that drive impact

    Generative AI could revolutionize your content creation, personalization and customer support. But can your data ecosystem keep up? Find out what it will take to sustain your innovation in this eBook.

    You’ll learn how M&E companies have used AI to:

    • Increase revenue by 8%–10%
    • Boost sales by 15%–25%
    • Achieve a 30%–40% better return on ad spend
    • Run personalization models with up to 97% accuracy

    By registering, I agree to the processing of my personal data by Databricks in accordance with their Privacy Policy. I can update my preferences at any time.

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