Book Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python PDF Download - Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel
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Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python
Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel
Page: 720
Format: pdf, ePub, mobi, fb2
ISBN: 9781394286799
Publisher: Wiley
Download or Read Online Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python Free Book (PDF ePub Mobi) by Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel
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Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python is a comprehensive introduction to and an overview of the methods that underlie modern AI. This best-selling textbook covers both statistical and machine learning (AI) algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, network analytics and generative AI. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second Python edition of Machine Learning for Business Analytics. This edition also includes: A new chapter on generative AI (large language models or LLMs, and image generation) An expanded chapter on deep learning A new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter of cases demonstrating applications for the machine learning techniques End-of-chapter exercises with data A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in AI, data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.
Data Mining for Business Analytics: Concepts, Techniques and .
It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, .
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Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods.
Machine Learning for Business Analytics: Concepts, Techniques .
Machine Learning for Business Analytics: Concepts, Techniques and Applications in RapidMiner ; Edition: 1 ; Publisher: Wiley ; Format: Hardcover (736 pages) .
[PDF] Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow
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Machine Learning for Business Analytics : Concepts, Techniques .
Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python is a comprehensive introduction to and an overview of the methods .
Machine Learning for Business Analytics: Concepts, Techniques .
It covers various aspects of business analytics and machine learning, including definitions, processes, and applications using RapidMiner. Additionally, it .
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Apply machine learning methods in Python to classify songs into genres. machine learning workflows and how to tie them back to business applications.
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It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, .
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Application of machine learning methods to large databases is called data mining. In retail business, machine learning is used to study consumer behaviour.