Machine Learning Upgrade

A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure

de

,

Éditeur :

Wiley


Paru le : 2024-07-29



eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
36,08

Téléchargement immédiat
Dès validation de votre commande
Ajouter à ma liste d'envies
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

Description

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.
Pages
240 pages
Collection
n.c
Parution
2024-07-29
Marque
Wiley
EAN papier
9781394249633
EAN PDF
9781394249664

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
240
Taille du fichier
5243 Ko
Prix
36,08 €
EAN EPUB
9781394249640

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
240
Taille du fichier
5233 Ko
Prix
36,08 €

Suggestions personnalisées