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Practical Machine Learning on Databricks

You're reading from Practical Machine Learning on Databricks Seamlessly transition ML models and MLOps on Databricks

Product type Paperback

Published in Nov 2023

Publisher Packt

ISBN-13 9781801812030

Length 244 pages

Edition 1st Edition

Languages

Python

Tools

MLOps

Concepts

Data Science

Author (1):

Debu Sinha

View More author details

Table of Contents (16) Chapters

Preface

1. Part 1: Introduction

2. Chapter 1: The ML Process and Its Challenges FREE CHAPTER

3. Chapter 2: Overview of ML on Databricks

4. Part 2: ML Pipeline Components and Implementation

5. Chapter 3: Utilizing the Feature Store

6. Chapter 4: Understanding MLflow Components on Databricks

7. Chapter 5: Create a Baseline Model Using Databricks AutoML

8. Part 3: ML Governance and Deployment

9. Chapter 6: Model Versioning and Webhooks

10. Chapter 7: Model Deployment Approaches

11. Chapter 8: Automating ML Workflows Using Databricks Jobs

12. Chapter 9: Model Drift Detection and Retraining

13. Chapter 10: Using CI/CD to Automate Model Retraining and Redeployment

14. Index

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15. Other Books You May Enjoy

Summary

In this chapter, we got a deeper understanding of feature stores, the problems they solve, and a detailed look into the feature store implementation within the Databricks environment. We also went through an exercise to register our first feature table. This will enable us to utilize the feature table to create our first ML model as we discussed in the MLFlow chapter.

Next, we will cover MLFlow in detail.

The rest of the chapter is locked

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Authors (1)

Debu Sinha

Debu Sinha

Debu is an experienced Data Science and Engineering leader with deep expertise in Software Engineering and Solutions Architecture. With over 10 years in the industry, Debu has a proven track record in designing scalable Software Applications, Big Data, and Machine Learning systems. As Lead ML Specialist on the Specialist Solutions Architect team at Databricks, Debu focuses on AI/ML use cases in the cloud and serves as an expert on LLMs, Machine Learning, and MLOps. With prior experience as a startup co-founder, Debu has demonstrated skills in team-building, scaling, and delivering impactful software solutions. An established thought leader, Debu has received multiple awards and regularly speaks at industry events.

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