Browsing by Subject "Machine learning"
Now showing items 1-14 of 14
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Artificial intelligence : with an introduction to machine learning
(CRC Press, 2018)The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based ... -
Blockchain, big data and machine learning : trends and applications
(CRC Press, 2020)"Present book covers new paradigms in Blockchain, big data and machine learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data ... -
Data analytics for business : lessons for sales, marketing, and strategy
(Routledge, 2023)"Interest in applying analytics, machine learning, and artificial intelligence to sales and marketing has grown dramatically, with no signs of slowing down. This book provides essential guidance to apply advanced analytics ... -
Deep learning
(The MIT Press, 2019)Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products ... -
Designing Machine Learning Systems
(O' Reilly, 2022) -
Machine learning
(McGraw-Hill, 1997)This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and ... -
Machine learning : algorithms and applications
(CRC Press, 2017)Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the ... -
Machine learning for algorithmic trading : predictive models to extract signals from market and alternative data for systematic trading strategies with Python
(Packt Publishing, 2020)This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from ... -
Managing Machine Learning Projects
(2023)Anyone who’s written a book knows it’s an unreasonably hard thing to do. I’ve needed a lot of help. Doug Rudder, my editor, and the team at Manning exceeded expectations and helped me transform a huge random mess of a ... -
Marketing analytics : a machine learning approach
(Apple Academic Press Inc., 2023)"With businesses becoming ever more competitive, marketing strategies need to be more precise and performance oriented. Companies are investing considerably in analytical infrastructure for marketing. This new volume, ... -
Neural networks and deep learning : a textbook
(Springer, 2018)This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding ... -
The elements of statistical learning : data mining, inference, and prediction
(Springer, 2017)This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use ...
