Description: Databricks ML in Action by Stephanie Rivera, Hayley Horn, Amanda Baker, Anastasia Prokaieva Explore the Databricks Data Intelligence Platform for developing and deploying ML data products. FORMAT Paperback CONDITION Brand New Publisher Description 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 onKey FeaturesBuild machine learning solutions faster than peers only using documentationEnhance or refine your expertise with tribal knowledge and concise explanationsFollow along with code projects provided in GitHub to accelerate your projectsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionDiscover what makes the Databricks Data Intelligence Platform the go-to choice for top-tier machine learning solutions. Written by a team of industry experts at Databricks with decades of combined experience in big data, machine learning, and data science, 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.Youll 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. Youll discover how to leverage the open-source Databricks platform to enhance learning, boost skills, and elevate productivity with supplemental resources.By the end of this book, youll have mastered the use of Databricks for data science, machine learning, and generative AI, enabling you to deliver outstanding data products.What you will learnSet up a workspace for a data team planning to perform data scienceMonitor data quality and detect driftUse autogenerated code for ML modeling and data explorationOperationalize ML with feature engineering client, AutoML, VectorSearch, Delta Live Tables, AutoLoader, and WorkflowsIntegrate open-source and third-party applications, such as OpenAIs ChatGPT, into your AI projectsCommunicate insights through Databricks SQL dashboards and Delta SharingExplore data and models through the Databricks marketplaceWho this book is forThis book is for machine learning engineers, data scientists, and technical managers seeking hands-on expertise in implementing and leveraging the Databricks Data Intelligence Platform and its Lakehouse architecture to create data products. Author Biography Stephanie Rivera has worked in big data and machine learning for 12 years. She collaborates with teams and companies as they design their Lakehouse as a Sr. Solutions Architect for Databricks. Previously Stephanie was the VP, Data Intelligence for a global company, taking in 20+ terabytes of data daily. She led the data science, data engineering, and business intelligence teams. Anastasia Prokaieva began her career 9 years ago as a research scientist at CEA (France), focusing on large data analysis and satellite data assimilation, treating terabytes of data. She has been working within the big data analysis and machine learning domain since then. In 2021, she joined Databricks and became the regional AI subject matter expert.On a daily basis, Anastasia consults Databricks users on best practices for implementing AI projects end-to-end. She also delivers training and workshops to democratize AI. Anastasia holds two MSc degrees in theoretical physics and energy science. Mandy Baker began her career in data 8 years ago. She loves leveraging her skills as a data scientist to orchestrate transformative journeys for companies across diverse industries as a Solutions Architect for Databricks. Her experiences have brought her from large corporations to small startups and everything in between. Mandy is a graduate of Carnegie Mellon University and the University of Washington. Hayley Horn started her data career 15 years ago as a data quality consultant on enterprise data integration projects. As a data scientist, she specialized in customer insights and strategy, and presented at Data Science and AI conferences in the US and Europe. She is currently a Sr. Solutions Architect for Databricks, with expertise in data science and technology modernization. A graduate of the MS Data Science program at Southern Methodist University in Dallas, Texas, USA, she is now a capstone advisor to students in their final semesters of the program. Table of Contents Table of ContentsGetting Started with This Book and Lakehouse ConceptsDesigning Databricks: Day OneBuilding Out Our Bronze LayerGetting to Know Your DataFeature Engineering on DatabricksSearching for a SignalProductionizing ML on DatabricksMonitoring, Evaluating, and More Details ISBN1800564899 Author Anastasia Prokaieva Publisher Packt Publishing Limited Year 2024 ISBN-13 9781800564893 Format Paperback Imprint Packt Publishing Limited Place of Publication Birmingham Country of Publication United Kingdom DEWEY 006.31 Audience Professional & Vocational Publication Date 2024-05-17 Subtitle Learn how Databricks supports the entire ML lifecycle end to end from data ingestion to the model deployment UK Release Date 2024-05-17 Pages 280 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:159982806;
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