Learning to Learn: Core Algorithms in AI and ML

In the rapidly evolving world of Artificial Intelligence (AI) and Machine Learning (ML) the ability to learn adapt and innovate is more vital than ever. As technology shapes every aspect of modern life—from healthcare and finance to agriculture and education—it becomes essential for the next generation of engineers data scientists and thinkers to grasp the fundamental algorithms that power intelligent systems.Learning to Learn: Core Algorithms in AI and ML is written with the goal of providing undergraduate students with a strong intuitive and application-oriented foundation in AI and ML. Our focus is not only to introduce algorithms but also to nurture critical thinking problem-solving skills and a mindset of continual learning—traits that define success in this dynamic field.This book covers a broad spectrum of AI/ML topics from supervised and unsupervised learning to deep learning reinforcement learning natural language processing model deployment and ethical AI. Special emphasis has been placed on real-world applications ensuring that readers can relate theoretical concepts to practical problems. With clear explanations visualizations and examples we aim to demystify complex topics and make AI and ML accessible to learners from diverse academic backgrounds.