The Machine Learning Solutions Architect Handbook: Create machine learning platforms to run solutions in an enterprise setting - Image 1

£62.40

Packt Publishing The Machine Learning Solutions Architect Handbook: Create machine learning platforms to run solutions in an enterprise setting

Name: The Machine Learning Solutions Architect Handbook: Create machine learning platforms to run solutions in an enterprise setting
Brand: Packt Publishing
Price: 62.4 GBP
Availability: InStock

E-business

Same price for 4 weeks. Today is much like next week.

£62 for 31 days straight · last change was Jan 2026

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 384 days • 384 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 384 days • 5 price ranges

Days at Price

Current Price

Price Analysis

Most common range: £57-62 (181 days, 47.1%)

Price range: £40 - £68

Price levels: 5 price ranges over 384 days

Description

Build highly secure and scalable machine learning platforms to support the fast-paced adoption of machine learning solutions Key Features Explore different ML tools and frameworks to solve large-scale machine learning challenges in the cloud Build an efficient data science environment for data exploration, model building, and model training Learn how to implement bias detection, privacy, and explainability in ML model development Book Description With a highly scalable machine learning (ML) platform, organizations can quickly scale the delivery of ML products for faster business value realization, so there is a huge demand for skilled ML solutions architects in different industries. This hands-on ML book takes you through the design patterns, architectural considerations, and the latest technology that you need to know to become a successful ML solutions architect. You'll start by understanding ML fundamentals and how ML can be applied to real-world business problems. Once you've explored some of the leading ML algorithms for solving different types of problems, the book will help you get to grips with data management and using ML libraries such as TensorFlow and PyTorch. You'll learn how to use open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines and then advance to building an enterprise ML architecture using Amazon Web Services (AWS) services. You'll then cover security and governance considerations, advanced ML engineering techniques, and how to apply bias detection, explainability, and privacy in ML model development. Finally, you'll get acquainted with AWS AI services and their applications in real-world use cases. By the end of this book, you'll be able to design and build an ML platform to support common use cases and architecture patterns. What you will learn Apply ML methodologies to solve business problems Design a practical enterprise ML platform architecture Implement MLOps for ML workflow automation Build an end-to-end data management architecture using AWS Train large-scale ML models and optimize model inference latency Create a business application using an AI service and a custom ML model Use AWS services to detect data and model bias and explain models Who this book is for This book is for data scientists, data engineers, cloud architects, and machine learning enthusiasts who want to become machine learning solutions architects. Basic knowledge of the Python programming language, AWS, linear algebra, probability, and networking concepts is assumed. Table of Contents Machine Learning and Machine Learning Solutions Architecture Business Use Cases for Machine Learning Machine Learning Algorithms Data Management for Machine Learning Open Source Machine Learning Libraries Kubernetes Container Orchestration Infrastructure Management Open Source Machine Learning Platforms Building a Data Science Environment Using AWS ML Services Building an Enterprise ML Architecture with AWS ML Services Advanced ML Engineering ML Governance, Bias, Explainability, and Privacy Building ML Solutions with AWS AI Services

Product Specifications

Brand: Packt Publishing
Format: Paperback
ASIN: 1801072167
Category: Books > Subjects > Business, Finance & Law > E-Commerce > E-business
Domain: Amazon UK
Release Date: 21 January 2022
Listed Since: 19 August 2021

Barcode

No barcode data available

Packt Publishing The Machine Learning Solutions Architect Handbook: Create machine learning platforms to run solutions in an enterprise setting

Same price for 4 weeks. Today is much like next week.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

AWS Certified Machine Learning Study Guide: Specialty (MLS-C01) Exam

Practical Machine Learning with AWS: Process, Build, Deploy, and Productionize Your Models Using AWS

Platform and Model Design for Responsible AI: Design and build resilient, private, fair, and transparent machine learning models

Azure Data Scientist Associate Certification Guide: A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam

AWS Certified Machine Learning Engineer Study Guide: Associate (MLA-C01) Exam (Sybex Study Guide)

AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide: The definitive guide to passing the MLS-C01 exam on the very first attempt

Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python

The Definitive Guide to Machine Learning Operations in AWS: Machine Learning Scalability and Optimization with AWS

Machine Learning for Oracle Database Professionals: Deploying Model-Driven Applications and Automation Pipelines

Mastering Java Machine Learning: A Java developer's guide to implementing machine learning and big data architectures

Practical Machine Learning for Data Analysis Using Python

Machine Learning with Amazon SageMaker Cookbook: 80 proven recipes for data scientists and developers to perform machine learning experiments and deployments

Practical Machine Learning with Python: A Problem-Solver's Guide to Building Real-World Intelligent Systems

Machine Learning Production Systems: Engineering Machine Learning Models and Pipelines

Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning

Official Google Cloud Certified Professional Machine Learning Engineer Study Guide (Sybex Study Guide)

Machine Learning and Artificial Intelligence: Concepts, Algorithms and Models

Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition

Applied Machine Learning for Data Science Practitioners

Scalable AI and Design Patterns: Design, Develop, and Deploy Scalable AI Solutions

Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions (Tech Today)

Python Machine Learning Case Studies: Five Case Studies for the Data Scientist

Machine Learning and Artificial Intelligence

A Greater Foundation for Machine Learning Engineering: The Hallmarks of the Great Beyond in Pytorch, R, Tensorflow, and Python