Isbn: 9781394249633 - machine learning upgrade: a data scientist's guide to mlops, llms, and ml infrastructure (32 risultati)

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New. 1st edition NO-PA16APR2015-KAP.

Paperback. Condizione: New. A much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), machine learning, and data science. This groundbreaking book will change the way that you view the pipeline of data science. The authors provide an introduction to modern machine learning, showing you how it can be viewed as a holistic, end-to-end system-not just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn't been codified yet, enabling you to forge the future using emerging best practices. Gain an understanding of the intersection between large language models and unstructured dataFollow the process of building an LLM-powered application while leveraging MLOps techniques such as data versioning and experiment trackingDiscover best practices for training, fine tuning, and evaluating LLMsIntegrate LLM applications within larger systems, monitor their performance, and retrain them on new data This book is indispensable for data professionals and business leaders looking to understand LLMs and the entire data science pipeline.…

Paperback. Condizione: New. A much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), machine learning, and data science. This groundbreaking book will change the way that you view the pipeline of data science. The authors provide an introduction to modern machine learning, showing you how it can be viewed as a holistic, end-to-end system-not just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn't been codified yet, enabling you to forge the future using emerging best practices. Gain an understanding of the intersection between large language models and unstructured dataFollow the process of building an LLM-powered application while leveraging MLOps techniques such as data versioning and experiment trackingDiscover best practices for training, fine tuning, and evaluating LLMsIntegrate LLM applications within larger systems, monitor their performance, and retrain them on new data This book is indispensable for data professionals and business leaders looking to understand LLMs and the entire data science pipeline.…

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: new.

Paperback. Condizione: new. Paperback. A much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), machine learning, and data science. This groundbreaking book will change the way that you view the pipeline of data science. The authors provide an introduction to modern machine learning, showing you how it can be viewed as a holistic, end-to-end systemnot just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn't been codified yet, enabling you to forge the future using emerging best practices. Gain an understanding of the intersection between large language models and unstructured dataFollow the process of building an LLM-powered application while leveraging MLOps techniques such as data versioning and experiment trackingDiscover best practices for training, fine tuning, and evaluating LLMsIntegrate LLM applications within larger systems, monitor their performance, and retrain them on new data This book is indispensable for data professionals and business leaders looking to understand LLMs and the entire data science pipeline. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condizione: New.

Condizione: New.

Paperback. Condizione: New.

Condizione: New. In English.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: Brand New. 256 pages. 6.00x0.60x8.90 inches. In Stock.

Condizione: New.

Condizione: 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.

Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condizione: New.

Condizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.

Condizione: New. Brand new! Please provide a physical shipping address.

Condizione: NEW.

Taschenbuch. Condizione: Neu. Neuware - A much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), machine learning, and data science. This groundbreaking book will change the way that you view the pipeline of data science. The authors provide an introduction to modern machine learning, showing you how it can be viewed as a holistic, end-to-end system-not just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn't been codified yet, enabling you to forge the future using emerging best practices. - Gain an understanding of the intersection between large language models and unstructured data - Follow the process of building an LLM-powered application while leveraging MLOps techniques such as data versioning and experiment tracking - Discover best practices for training, fine tuning, and evaluating LLMs - Integrate LLM applications within larger systems, monitor their performance, and retrain them on new data This book is indispensable for data professionals and business leaders looking to understand LLMs and the entire data science pipeline.…

Paperback. Condizione: New. A much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), machine learning, and data science. This groundbreaking book will change the way that you view the pipeline of data science. The authors provide an introduction to modern machine learning, showing you how it can be viewed as a holistic, end-to-end system-not just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn't been codified yet, enabling you to forge the future using emerging best practices. Gain an understanding of the intersection between large language models and unstructured dataFollow the process of building an LLM-powered application while leveraging MLOps techniques such as data versioning and experiment trackingDiscover best practices for training, fine tuning, and evaluating LLMsIntegrate LLM applications within larger systems, monitor their performance, and retrain them on new data This book is indispensable for data professionals and business leaders looking to understand LLMs and the entire data science pipeline.…

Paperback. Condizione: new. Paperback. A much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), machine learning, and data science. This groundbreaking book will change the way that you view the pipeline of data science. The authors provide an introduction to modern machine learning, showing you how it can be viewed as a holistic, end-to-end systemnot just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn't been codified yet, enabling you to forge the future using emerging best practices. Gain an understanding of the intersection between large language models and unstructured dataFollow the process of building an LLM-powered application while leveraging MLOps techniques such as data versioning and experiment trackingDiscover best practices for training, fine tuning, and evaluating LLMsIntegrate LLM applications within larger systems, monitor their performance, and retrain them on new data This book is indispensable for data professionals and business leaders looking to understand LLMs and the entire data science pipeline. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Paperback. Condizione: new. Paperback. A much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), machine learning, and data science. This groundbreaking book will change the way that you view the pipeline of data science. The authors provide an introduction to modern machine learning, showing you how it can be viewed as a holistic, end-to-end systemnot just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn't been codified yet, enabling you to forge the future using emerging best practices. Gain an understanding of the intersection between large language models and unstructured dataFollow the process of building an LLM-powered application while leveraging MLOps techniques such as data versioning and experiment trackingDiscover best practices for training, fine tuning, and evaluating LLMsIntegrate LLM applications within larger systems, monitor their performance, and retrain them on new data This book is indispensable for data professionals and business leaders looking to understand LLMs and the entire data science pipeline. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condizione: New Books. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Condizione: New. A much-needed guide to implementing new technology in workspacesFrom experts in the field comes Machine Learning Upgrade: A Data Scientist s Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices a.

Paperback. Condizione: New. A much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), machine learning, and data science. This groundbreaking book will change the way that you view the pipeline of data science. The authors provide an introduction to modern machine learning, showing you how it can be viewed as a holistic, end-to-end system-not just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn't been codified yet, enabling you to forge the future using emerging best practices. Gain an understanding of the intersection between large language models and unstructured dataFollow the process of building an LLM-powered application while leveraging MLOps techniques such as data versioning and experiment trackingDiscover best practices for training, fine tuning, and evaluating LLMsIntegrate LLM applications within larger systems, monitor their performance, and retrain them on new data This book is indispensable for data professionals and business leaders looking to understand LLMs and the entire data science pipeline.…