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Packt Practical Machine Learning on Databricks: Seamlessly transition ML models and MLOps on Databricks

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المواصفات

الناشر	Packt Publishing
رقم الكتاب المعياري الدولي 10	1801812039
وصف الكتاب	Take your machine learning skills to the next level by mastering databricks and building robust ML pipeline solutions for future ML innovationsKey FeaturesLearn to build robust ML pipeline solutions for databricks transitionMaster commonly available features like AutoML and MLflowLeverage data governance and model deployment using MLflow model registryPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionUnleash the potential of databricks for end-to-end machine learning with this comprehensive guide, tailored for experienced data scientists and developers transitioning from DIY or other cloud platforms. Building on a strong foundation in Python, Practical Machine Learning on Databricks serves as your roadmap from development to production, covering all intermediary steps using the databricks platform.You'll start with an overview of machine learning applications, databricks platform features, and MLflow. Next, you'll dive into data preparation, model selection, and training essentials and discover the power of databricks feature store for precomputing feature tables. You'll also learn to kickstart your projects using databricks AutoML and automate retraining and deployment through databricks workflows.By the end of this book, you'll have mastered MLflow for experiment tracking, collaboration, and advanced use cases like model interpretability and governance. The book is enriched with hands-on example code at every step. While primarily focused on generally available features, the book equips you to easily adapt to future innovations in machine learning, databricks, and MLflow.What you will learnTransition smoothly from DIY setups to databricksMaster AutoML for quick ML experiment setupAutomate model retraining and deploymentLeverage databricks feature store for data prepUse MLflow for effective experiment trackingGain practical insights for scalable ML solutionsFind out how to handle model drifts in production environmentsWho this book is forThis book is for experienced data scientists, engineers, and developers proficient in Python, statistics, and ML lifecycle looking to transition to databricks from DIY clouds. Introductory Spark knowledge is a must to make the most out of this book, however, end-to-end ML workflows will be covered. If you aim to accelerate your machine learning workflows and deploy scalable, robust solutions, this book is an indispensable resource.Table of ContentsML Process and ChallengesOverview of ML on DatabricksUtilizing Feature Store Understanding MLflow ComponentsCreate a Baseline Model for Bank Customer Churn Prediction Using AutoMLModel Versioning and WebhooksModel Deployment ApproachesAutomating ML Workflows Using the Databricks JobsModel Drift Detection for Our Churn Prediction Model and RetrainingCI/CD to Automate Model Retraining and Re-Deployment.
اللغة	English
عدد الصفحات	244 pages

رقم الكتاب المعياري الدولي 13	9781801812030
عن المؤلف	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.
الكاتب	Debu Sinha
تاريخ النشر	24 November 2023

Packt Practical Machine Learning on Databricks: Seamlessly transition ML models and MLOps on Databricks

192.00

 201