Machine Learning: For Business Applications
1st Edition
9364443535
·
9789364443531
© 2025 | Published: May 10, 2025
Overview:This book aims to serve as a textbook for a course on Machine Learning for Business Applications and related courses. It provides a comprehensive overview of how machine learning and deep learning can be used in various business analytics si…
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PART I Introduction to Machine Learning with Python and Orange
Chapter 1 Introduction to Python and Orange
Chapter 2 Data Preparation and Data Transformation
PART II Supervised Machine Learning with Python and Orange
Chapter 3 Fundamentals of Machine Learning
Chapter 4 Supervised Machine Learning
Chapter 5 Decision Tree and Ensemble Models
PART III Unsupervised Machine Learning and Deep Learning with Python and Orange
Chapter 6 Unsupervised Machine Learning
Chapter 7 Artificial Neural Networks and Deep Learning
PART IV Text Analytics Applications with Python and Orange
Chapter 8 Text Analytics
Chapter 9 Sentiment Analytics
PART V Data Accessibility and Ethical Issues for Machine Learning Applications
Chapter 10 Ethical Issues of Using AI/ML
Chapter 11 Social Media Analytics
Chapter 1 Introduction to Python and Orange
Chapter 2 Data Preparation and Data Transformation
PART II Supervised Machine Learning with Python and Orange
Chapter 3 Fundamentals of Machine Learning
Chapter 4 Supervised Machine Learning
Chapter 5 Decision Tree and Ensemble Models
PART III Unsupervised Machine Learning and Deep Learning with Python and Orange
Chapter 6 Unsupervised Machine Learning
Chapter 7 Artificial Neural Networks and Deep Learning
PART IV Text Analytics Applications with Python and Orange
Chapter 8 Text Analytics
Chapter 9 Sentiment Analytics
PART V Data Accessibility and Ethical Issues for Machine Learning Applications
Chapter 10 Ethical Issues of Using AI/ML
Chapter 11 Social Media Analytics
Overview:
This book aims to serve as a textbook for a course on Machine Learning for Business Applications and related courses. It provides a comprehensive overview of how machine learning and deep learning can be used in various business analytics situations. It equips the reader with the understanding of various tools like Jupyter Notebook (for python coding), and Orange (python-based GUI interface). This will help the reader to understand the application of various algorithms for performing analysis by using different real-life case studies and examples. With coverage of topics like Social Media Analytics, Text Mining, and Ethic of Data Mining with AI, this book will appeal to a wider range of audiences.
Key Features:
- Concise textbooks with case studies related to various business applications like Financial Analytics, HR Analytics etc.
- Provides detailed, step-by-step understanding about implementation of various machine learning algorithms
- Demonstrates the practical applicability of different algorithms with the use of examples, which will help students who require practical illustrations of how these algorithms might be used in actual business analytics situations
- Covers some of the important topics like text mining concepts and application, application of Machine Learning in social media analytics, ethics of data mining with AI, etc.
This book aims to serve as a textbook for a course on Machine Learning for Business Applications and related courses. It provides a comprehensive overview of how machine learning and deep learning can be used in various business analytics situations. It equips the reader with the understanding of various tools like Jupyter Notebook (for python coding), and Orange (python-based GUI interface). This will help the reader to understand the application of various algorithms for performing analysis by using different real-life case studies and examples. With coverage of topics like Social Media Analytics, Text Mining, and Ethic of Data Mining with AI, this book will appeal to a wider range of audiences.
Key Features:
- Concise textbooks with case studies related to various business applications like Financial Analytics, HR Analytics etc.
- Provides detailed, step-by-step understanding about implementation of various machine learning algorithms
- Demonstrates the practical applicability of different algorithms with the use of examples, which will help students who require practical illustrations of how these algorithms might be used in actual business analytics situations
- Covers some of the important topics like text mining concepts and application, application of Machine Learning in social media analytics, ethics of data mining with AI, etc.