Hao benjamin (26 Ergebnisse)

Zustand: good. Signs of wear and consistent use.

Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Paperback. Zustand: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

Zustand: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

Zustand: As New. Unread copy in mint condition.

Zustand: New. Brand New.

paperback. Zustand: Fine.

Paperback. Zustand: new. New Copy. Customer Service Guaranteed.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Hardcover. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely. Nguyen, Nhat Hao (illustrator).

Zustand: new.

Hardback. Zustand: New. New copy - Usually dispatched within 4 working days.

Paperback. Zustand: Brand New. pap/psc edition. 278 pages. 9.25x7.50x0.50 inches. In Stock.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

paperback. Zustand: New. Special order direct from the distributor.

Zustand: New. 2026. 1st Edition. paperback. . . . . .

Zustand: New. 2026. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.

Zustand: NEW.

Buch. Zustand: Neu. Neuware - Machine learning models look great in not Elektronisches Buch, 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: Step-by-step ML pipeline assembly: A true 'from-scratch' playbook that assembles an end-to-end MLOps stack. Deploy machine learning models to production: Combine Kubeflow, MLflow, BentoML, Feast, and Evidently without vendor lock-in. Build end-to-end data pipelines: Move seamlessly from raw data to monitored, live predictions. Robust deployment patterns: Serve fast, scalable models that stay responsive under real traffic. Effective monitoring and explainability: Detect drift early and keep stakeholders confident. 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 Elektronisches Buch 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. …

Buch. Zustand: Neu. Build a Machine Learning Platform (From Scratch) | Benjamin Hao | Buch | Englisch | 2026 | Manning Publications | EAN 9781633437333 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Buch. Zustand: Neu. Neuware -Machine learning models look great in not Elektronisches Buch, 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: Step-by-step ML pipeline assembly: A true 'from-scratch' playbook that assembles an end-to-end MLOps stack. Deploy machine learning models to production: Combine Kubeflow, MLflow, BentoML, Feast, and Evidently without vendor lock-in. Build end-to-end data pipelines: Move seamlessly from raw data to monitored, live predictions. Robust deployment patterns: Serve fast, scalable models that stay responsive under real traffic. Effective monitoring and explainability: Detect drift early and keep stakeholders confident. 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 Elektronisches Buch 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. 504 pp. Englisch.…

paperback. Zustand: New. Ship out in 2 business day, And Fast shipping, Free Tracking number will be provided after the shipment.History of seismologyFour Satisfaction guaranteed,or money back.

Hardcover. Zustand: Brand New. 270 pages. 8.00x0.88x10.00 inches. In Stock. This item is printed on demand. Nguyen, Nhat Hao (illustrator).