Practical AI for Business Leaders, Product Managers, and Entrepreneurs

; Shirin Mojarad

Implementing advanced analytics at scale in a competitive landscape requires the speed, agility, and mindset of an entrepreneur. It is here that organizations in the future will gain an edge. This book provides the practical guidance and theoretical background necessary to implement advanced analytics in mid- to large organizations. Les mer
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Paperback
Legg i
Vår pris: 659,-

(Paperback) Fri frakt!
Leveringstid: Usikker levering*
*Vi bestiller varen fra forlag i utlandet. Dersom varen finnes, sender vi den så snart vi får den til lager

Om boka

Implementing advanced analytics at scale in a competitive landscape requires the speed, agility, and mindset of an entrepreneur. It is here that organizations in the future will gain an edge. This book provides the practical guidance and theoretical background necessary to implement advanced analytics in mid- to large organizations. The theoretical component draws from the best academic research in management science, computer science, and behavioral economics. The practical component provides design patterns and case studies for implementing big data at scale in complex organizations. The design patterns take the mindset of an entrepreneur having to execute with speed and agility against the backdrop of business, technical, and stakeholder complexity.



Readers will learn:



Principal characteristics of Advanced Analytics and Big Data in the Enterprise
Business and technical strategies for fast, affordable, and efficient implementation
Strategy and implementation tactics from the point of an "entrepreneur" within a large organization
Academic research rationale behind the strategies
Best practices in the form of case studies

Fakta

Innholdsfortegnelse

Introduction

What is AI and why it is at the center of major business transformation?

How is it related to machine learning?

What is deep learning, and how is it related to ML?

Why is it important?

How the book is organized

Who is the audience?


Section 1: Machine Learning Chapter 1.1, introduction, machine learning, different types of machine learning

Chapter 1.2, Machine Learning Technical Overview

Chapter 1.3, Hands-On Machine Learning with Scikit Learn

Chapter 1.4, Advanced Topics/flavors of Machine learning

Appendix: mathematical interlude




Section 2: Deep Learning

Chapter 2.1, introduction (what is it, why is it important)

Chapter 2.2, Deep Learning Technical Overview

Chapter 2.3, Hands-On Deep Learning with Keras

Chapter 2.4, Advanced Topics/flavors of deep learning

Appendix: mathematical interlude




Section 3: Putting AI into Practice: Innovation Framework

Chapter 3.1: Diffusion and Dynamics of Innovation

Chapter 3.2: Managing an Innovation Portfolio

Om forfatteren

Alfred Essa, Vice President, Analytics and R&D at McGraw-Hill Education; Shirin Mojarad, Data Scientist, Massachusetts, USA