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Can I read Databricks ML in Action : Learn How Databricks Supports the Entire ML Lifecycle End to End From Data Ingestion to the Model Deployment on EtoBox?
Databricks ML in Action : Learn How Databricks Supports the Entire ML Lifecycle End to End From Data Ingestion to the Model Deployment by Hayley Horn, Anastasia Prokaieva, Amanda Baker, Stephanie Rivera is a nonfiction available to read on EtoBox.
What is Databricks ML in Action : Learn How Databricks Supports the Entire ML Lifecycle End to End From Data Ingestion to the Model Deployment about?
Get to grips with autogenerating code, deploying ML algorithms, and leveraging various ML lifecycle features on the Databricks Platform, guided by best practices and reusable code for you to try, alter, and build on Key Features Build machine learning solutions faster than peers only using documentation Enhance or refine your expertise with tribal knowledge and concise explanations Follow along with code projects provided in GitHub to accelerate your projects Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDiscover what makes the Databricks Data Intelligence Platform the go-to choice for top-tier machine learning solutions. 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
Who reads Databricks ML in Action : Learn How Databricks Supports the Entire ML Lifecycle End to End From Data Ingestion to the Model Deployment?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Hayley Horn, Anastasia Prokaieva, Amanda Baker, Stephanie Rivera
- Publisher
- Packt Publishing - ebooks Account
- Published
- 2024
- Language
- EN
- ISBN
- 9781800564008
- Category
- nonfiction
- Subjects
- Science, Computer Science, Stem
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