Artificial Intelligence and Machine Learning
Description
This book is a comprehensive exploration of the dynamic and transformative world of AI and ML. It takes readers on a journey through the foundational principles, diverse algorithms, and real-world applications of these cutting-edge technologies. It delves into the ethical considerations, challenges, and the potential impact on our future, offering a holistic perspective on the ever-evolving landscape of artificial intelligence and machine learning. Whether the readers are a novice looking for a comprehensive introduction or an expert seeking to delve deeper, this book provides insights, knowledge, and inspiration for embracing the limitless possibilities of AI and ML. Join the authors on a captivating voyage as they unravel the mysteries, unveil the innovations, and chart the course for the future of technology.
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Deepti Chopra holds a Ph.D. in Natural Language Processing from Banasthali Vidyapith. She is currently working as an Assistant Professor at the Vivekananda Institute of Professional Studies, Technical Campus, School of Engineering, Delhi. Dr. Chopra is the author of seven books and two MOOCs. Two of her books have been translated into Chinese, and one into Korean. She holds two Australian patents and one Indian patent. Dr. Chopra has published several papers in reputed international conferences and journals. Her areas of interest include artificial intelligence, natural language processing, and computational linguistics. Her primary research focuses on machine translation, information retrieval, and cognitive computing.
Roopal Khurana is an Assistant General Manager at RailTel Corporation of India Ltd., New Delhi, India. He currently works in the field of Data Networking and MPLS Technology. He holds a B.Tech. in Computer Science and Engineering from GLA University, Mathura, India. He has previously worked with companies such as Orange and Bharti Airtel. He is also the author of three books in the field of Computer Science and Information Technology.
Content
Chapter 1. Foundations of Artificial Intelligence and Machine Learning.- Chapter 2. Machine Learning Algorithms and Techniques.- Chapter 3. AI Applications in Real World Scenarios.- Chapter 4. Ethical Considerations and Challenges.- Chapter 5. The Future of AI and ML.- Chapter 6. Deep Learning and Neural Networks.- Chapter 7. Reinforcement Learning and Robotics.- Chapter 8. Time Series Analysis and Forecasting.- Chapter 9. Explainability and Interpretability in AI.- Chapter 10. AI and ML for Business and Decision Making.- Chapter 11. AI in Social Sciences and Humanities.- Chapter 12. Challenges and Limitations of AI and ML.- Chapter 13. The Road Ahead Advances and Future Directions.