Machine Learning Upgrade
A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure
By Caleb Kaiser, Kristen Kehrer | Publisher: Wiley
About the book
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.
Editions of Machine Learning Upgrade
- Paperback
- ISBN 9781394249633
- EBook
- ISBN 9781394249664
- EBook
- ISBN 9781394319763
- EBook
- ISBN 9781394249640
Read an Excerpt
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.
Frequently Asked Questions
What is Machine Learning Upgrade about?
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.
What core themes, tropes, or subjects are explored in Machine Learning Upgrade?
Computing and Information Technology > Computer science > Artificial intelligence (AI) > Machine learning
Where can I read a sample of Machine Learning Upgrade?
You can read an official preview of the few pages here https://www.book2look.com/book/9781394249633
Who is/are the Author/s of the book Machine Learning Upgrade?
Caleb Kaiser, Kristen Kehrer
Who is the Publisher of the book Machine Learning Upgrade?
Wiley
What are the ISBN numbers for the physical and digital editions?
Machine Learning Upgrade is available as paperback(ISBN 9781394249633) and ebook(ISBN 9781394249664) and ebook(ISBN 9781394319763) and ebook(ISBN 9781394249640)
Where can I buy Machine Learning Upgrade online or support local independent bookshops?
You can buy Machine Learning Upgrade from below
Where can I buy Machine Learning Upgrade?