Sinha Practical Machine Learning on Databricks

Seamlessly transition ML models and MLOps on Databricks
1. Auflage 2023
ISBN: 978-1-80181-829-2
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 244 Seiten

No detailed description available for "Practical Machine Learning on Databricks".

Autoren/Hrsg.

Sinha, Debu

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Warehouse

Inhaltsverzeichnis

Table of Contents - ML Process and Challenges
- Overview of ML on Databricks
- Utilizing Feature Store
- Understanding MLflow Components
- Create a Baseline Model for Bank Customer Churn Prediction Using AutoML
- Model Versioning and Webhooks
- Model Deployment Approaches
- Automating ML Workflows Using the Databricks Jobs
- Model Drift Detection for Our Churn Prediction Model and Retraining
- CI/CD to Automate Model Retraining and Re-Deployment.

Über Autor(innen)

Sinha Debu:
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.