Building Intelligent Systems: A Guide to Machine Learning Engineering

Apress Building Intelligent Systems:A Guide to Machine Learning Engineering.pdf

Book Description

Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success.

This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems.

Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world.

What You'll Learn

Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for success

Design an intelligent user experience: Achieve your objectives and produce data to help make the Intelligent System better over time

Implement an Intelligent System: Execute, manage, and measure Intelligent Systems in practice

Create intelligence: Use different approaches, including machine learning

Orchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want

This Book Is For

Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems.

Table of Contents

Part I: Approaching an Intelligent Systems Project

Chapter 1: Introducing Intelligent Systems

Chapter 2: Knowing When to Use Intelligent Systems

Chapter 3: A Brief Refresher on Working with Data

Chapter 4: Defining the Intelligent System’s Goals

Part II: Intelligent Experiences

Chapter 5: The Components of Intelligent Experiences

Chapter 6: Why Creating Intelligent Experiences Is Hard

Chapter 7: Balancing Intelligent Experiences

Chapter 8: Modes of Intelligent Interaction

Chapter 9: Getting Data from Experience

Chapter 10: Verifying Intelligent Experiences

Part III: Implementing Intelligence

Chapter 11: The Components of an Intelligence Implementation

Chapter 12: The Intelligence Runtime

Chapter 13: Where Intelligence Lives

Chapter 14: Intelligence Management

Chapter 15: Intelligent Telemetry

Part IV: Creating Intelligence

Chapter 16: Overview of Intelligence

Chapter 17: Representing Intelligence

Chapter 18: The Intelligence Creation Process

Chapter 19: Evaluating Intelligence

Chapter 20: Machine Learning Intelligence

Chapter 21: Organizing Intelligence

Part V: Orchestrating Intelligent Systems

Chapter 22: Overview of Intelligence Orchestration

Chapter 23: The Intelligence Orchestration Environment

Chapter 24: Dealing with Mistakes

Chapter 25: Adversaries and Abuse

Chapter 26: Approaching Your Own Intelligent System

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