Machine Learning for Managers

Regular price €43.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Paul Geertsema
Animal Kingdom
artificial intelligence
Author_Paul Geertsema
Average Model Prediction
Business Case
business intelligence
business operations
Category=KJ
Category=UYQM
clustering techniques
data analytics
data science
Data Set
Decentralized Autonomous Organizations
deep learning
Dimensionality Reduction
Distributed Version Control System
Entire Training Data Set
eq_bestseller
eq_business-finance-law
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
explainable artificial intelligence
Hidden Node
Hyperparameter Tuning
machine learning project lifecycle
Machines Learn Decision Trees
Ml Algorithm
Ml Model
Ml System
neural network fundamentals
organisational data modelling
predictive analytics methods
Principal Component PCA
project management in AI
Proxy Models
Random Forests
RNN Architecture
Roc Curve
Shapley Values
Traffic Flow Model
Tree Predictors
Unsupervised Machine Learning
Version Control
Vice Versa

Product details

  • ISBN 9781032362427
  • Weight: 300g
  • Dimensions: 156 x 234mm
  • Publication Date: 19 Jun 2023
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
Secure checkout Fast Shipping Easy returns

Machine learning can help managers make better predictions, automate complex tasks and improve business operations. Managers who are familiar with machine learning are better placed to navigate the increasingly digital world we live in. There is a view that machine learning is a highly technical subject that can only be understood by specialists. However, many of the ideas that underpin machine learning are straightforward and accessible to anyone with a bit of curiosity. This book is for managers who want to understand what machine learning is about, but who lack a technical background in computer science, statistics or math.

The book describes in plain language what machine learning is and how it works. In addition, it explains how to manage machine learning projects within an organization.

This book should appeal to anyone that wants to learn more about using machine learning to drive value in real-world organizations.

Paul Geertsema is an academic and consultant in the areas of finance, data science and machine learning. His research involves the application of contemporary machine learning methods to solving problems in finance and business. He teaches Modern Investment Theory and Management (final-year undergraduate) and Financial Machine Learning (postgraduate) at the University of Auckland. Dr Geertsema has published in numerous international peer-reviewed journals, including the Journal of Accounting Research and the Journal of Banking and Finance, and serves on the board of the AI Researchers Association. Prior to his return to academia, Dr Geertsema worked at Barclays Capital as a derivatives trader in Hong Kong and as a sell-side research analyst in London.

More from this author