Description
Ane Books Pvt Ltd Artificial Intelligence and Machine Learning 2023 by Deepti Chopra
This book is a comprehensive exploration of the dynamic and transformative world of AI and ML. It takes you 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 you're 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 us on a captivating voyage as we unravel the mysteries, unveil the innovations, and chart the course for the future of technology. Key Features: ►Real-World Applications: Explore how AI and Machine Learning are revolutionizing industries such as healthcare, finance, and transportation through practical case studies and examples. ►Hands-On Learning: Gain practical skills through step-by-step tutorials, code snippets, and exercises that reinforce your understanding and enable you to build your own intelligent systems. ►Ethical Considerations: Dive into the ethical implications of AI, including bias, privacy, and transparency, and learn how to develop responsible and fair AI solutions. ►Cutting-Edge Insights: Stay ahead of the curve with the latest advancements, emerging trends, and future directions in AI and Machine Learning, ensuring you are well-equipped for the challenges and opportunities that lie ahead. Contents : 1. Foundations of Artificial Intelligence and Machine Learning 2. Machine Learning Algorithms and Techniques 3. AI Applications in Real World Scenarios 4. Ethical Considerations and Challenges 5. The Future of AI and ML 6. Deep Learning and Neural Networks 7. Reinforcement Learning and Robotics 8. Time Series Analysis and Forecasting 9. Explainability and Interpretability in AI 10. AI and ML