Data Mining Vs Machine Learning
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Fundamentals of Data Science DataMining MachineLearning DeepLearning and IoTs
Author: Dr. P. Kavitha
language: en
Publisher: Leilani Katie Publication
Release Date: 2023-12-23
Dr. P. Kavitha, Associate Professor, Department of Computer Science, Sri Ramakrishna College of Arts & Science, Coimbatore, Tamil Nadu, India. Mr. P. Jayasheelan, Assistant Professor, Department of Computer Science, Sri Krishna Aditya College of arts and Science, Coimbatore, Tamil Nadu, India. Ms. C. Karpagam, Assistant Professor, Department of Computer Science with Data Analytics, Dr. N.G.P. Arts and Science College, Coimbatore, Tamil Nadu, India. Dr. K. Prabavathy, Assistant Professor, Department of Data Science and Analytics, Sree Saraswathi Thyagaraja College, Pollachi, Coimbatore, Tamil Nadu, India.
Data Classification and Incremental Clustering in Data Mining and Machine Learning
Author: Sanjay Chakraborty
language: en
Publisher: Springer Nature
Release Date: 2022-05-10
This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.
Artificial Intelligence And Machine Learning
Author: P. Kalyani
language: en
Publisher: Academic Guru Publishing House
Release Date: 2023-11-03
“Artificial Intelligence and Machine Learning: Navigating the Future” is a thorough look at how two of the most important tools of our time are changing the world. This book, written by experts in the field, goes beyond the complicated topics of AI and ML to give readers a clear and easy-to-understand path to understand the difficulties, uses, and moral concerns of these cutting-edge technologies. The first part of the book gives an overview of how AI and ML have changed over time, focusing on the theoretical foundations that have turned them from vague ideas to important parts of our digital world. From early algorithms to modern deep learning systems, readers learn about the processes that make smart decisions and solve problems. The book goes beyond academic ideas and looks at how AI and ML are being used in the real world to show how they are changing businesses and our everyday lives. These pages give you useful information about the technologies that will shape our future, whether they are improving healthcare monitoring, making business operations run more smoothly, or changing the way we use technology. When AI is being developed, ethical concerns are very important. This shows how responsible creation is. In this book, the effects of AI and ML on society are looked at, including problems of fairness, openness, and responsibility. People who read this are urged to think about the moral aspects of technology. This helps people value both technical progress and its moral effects.