Build a Machine Learning Platform (From Scratch)
Benjamin Tan Wei Hao
Sold by PBShop.store US, Wood Dale, IL, U.S.A.
AbeBooks Seller since 7 April 2005
New - Soft cover
Condition: New
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Quantity: 15 available
Add to basketSold by PBShop.store US, Wood Dale, IL, U.S.A.
AbeBooks Seller since 7 April 2005
Condition: New
Quantity: 15 available
Add to basketNew Book. Shipped from UK. Established seller since 2000.
Seller Inventory # PB-9781633437333
Machine learning models look great in notebooks, then collapse in production. Ready to build an ML platform that actually delivers? Here’s a step-by-step, project-driven guide to building an MLOps-ready platform from scratch.
Inside you’ll find:
Build a Machine Learning Platform (From Scratch) by Benjamin Tan Wei Hao, Shanoop Padmanabhan, and Varun Mallya delivers a practical field guide in print and eBook formats. Three veteran engineers lead you through every layer of modern MLOps.
The chapters construct two reference systems, an image classifier and a recommendation engine, while teaching orchestration, training, serving, and monitoring techniques. The actionable items for each concept include sample code, architecture diagrams, and checklists.
By the end of this book, you will end up with a reusable blueprint that slashes deployment time, reduces firefighting, and thrives with team growth. You will start shipping platforms that thrive.
Ideal for Python-savvy data scientists and software engineers eager to master production-quality machine learning.
Benjamin Tan Wei Hao is a product manager and principal engineer known for turning data into reliable ML delivery machines. With years leading platform builds, Benjamin distills deep MLOps experience into step-by-step guidance that helps readers ship scalable, maintainable models.
Shanoop Padmanabhan is a software engineering manager recognized for advancing autonomous-vehicle perception through robust ML platforms. He translates complex deployment challenges into replicable patterns.
Varun Mallya is a machine-learning engineer responsible for bank-wide ML platform stability and growth. With experience in scaling mission-critical models, Varun offers grounded insight on reliability and monitoring.
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