Building Machine Learning Powered Applications Going from Idea to Product by Emmanuel Ameisen PDF
Category: eBooks
- views: 115
- date: 26 July 2024
- posted by: BeMyLove

Building Machine Learning Powered Applications Going from Idea to Product by Emmanuel Ameisen PDF | 13.97 MB
260 Pages
Title: Building Machine Learning Powered Applications
Author: Emmanuel Ameisen
Description:
Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers—including experienced practitioners and novices alike—will learn the tools, best practices, and challenges involved in building a real-world ML application step by step.
Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies.
This book will help you:
Define your product goal and set up a machine learning problem
Build your first end-to-end pipeline quickly and acquire an initial dataset
Train and evaluate your ML models and address performance bottlenecks
Deploy and monitor your models in a production environment
DOWNLOAD:
https://rapidgator.net/file/0627dc647bdcbde0f604cee1d4b74e0e/Building_Machine_Learning_Powered_Applications__Going_from_Idea_to_Product_by_Emmanuel_Ameisen_PDF.rar
https://k2s.cc/file/1eeea25cc44a7/Building_Machine_Learning_Powered_Applications__Going_from_Idea_to_Product_by_Emmanuel_Ameisen_PDF.rar
Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers—including experienced practitioners and novices alike—will learn the tools, best practices, and challenges involved in building a real-world ML application step by step.
Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies.
This book will help you:
DOWNLOAD:
https://rapidgator.net/file/0627dc647bdcbde0f604cee1d4b74e0e/Building_Machine_Learning_Powered_Applications__Going_from_Idea_to_Product_by_Emmanuel_Ameisen_PDF.rar
https://k2s.cc/file/1eeea25cc44a7/Building_Machine_Learning_Powered_Applications__Going_from_Idea_to_Product_by_Emmanuel_Ameisen_PDF.rar
We need your support!
Make a donation to help us stay online
Bitcoin (BTC)
bc1q08g9d22cxkawsjlf8etuek2pc9n2a3hs4cdrld
Bitcoin Cash (BCH)
qqvwexzhvgauxq2apgc4j0ewvcak6hh6lsnzmvtkem
Ethereum (ETH)
0xb55513D2c91A6e3c497621644ec99e206CDaf239
Litecoin (LTC)
ltc1qt6g2trfv9tjs4qj68sqc4uf0ukvc9jpnsyt59u
USDT (ERC20)
0xb55513D2c91A6e3c497621644ec99e206CDaf239
USDT (TRC20)
TYdPNrz7v1P9riWBWZ317oBgJueheGjATm
Information |
|||
![]() |
Users of GUESTS are not allowed to comment this publication. | ||









