Machine Learning: Methodologies and Applications

Machine learning is a branch of artificial intelligence (AI) focused on developing algorithms that allow computers to learn from and make predictions or decisions based on data. It involves creating models that automatically improve their performance over time without being explicitly programmed. Key techniques in machine learning include supervised learning, where algorithms learn from labelled data and unsupervised learning, where they discover patterns in unlabeled data. Reinforcement learning is another approach where algorithms learn by interacting with an environment and receiving feedback. Machine learning finds applications in diverse fields like finance, healthcare and robotics, where it can analyse large datasets to uncover insights, make predictions or automate tasks. The goal is to enable computers to learn and adapt to new data, ultimately improving their ability to perform tasks that traditionally require human intelligence. This book unravels the recent studies in the field of machine learning. It presents research and studies performed by experts across the globe. This book will help new researchers by foregrounding their knowledge in this branch.