ARTIFICIAL INTELLIGENCE AND MACHINELEARNING: PRINCIPLE AND TECHNIQUES

₹ 759

Pay Now
Published Date: 2024-05-15
Author Name: Dr. Anil Pandurang Gaikwad , Prof. Krutika Balram Kakpure , Prof. Nikita Akshay Gosavi, Dr. Kishor Madhukar Dhole,

---

Artificial Intelligence (AI) and Machine Learning (ML) encompass a wide array of principles and techniques aimed at creating systems that can perform tasks typically requiring human intelligence. AI involves the development of algorithms that enable machines to mimic cognitive functions such as learning, reasoning, and problem-solving. Within this broad field, ML is a subset focused on the use of statistical methods and computational models to enable machines to learn from and make predictions based on data. Key techniques in ML include supervised learning, where models are trained on labeled data; unsupervised learning, which involves identifying patterns in unlabeled data; and reinforcement learning, where agents learn to make decisions by receiving rewards or penalties. These technologies drive innovations across various domains, from natural language processing and computer vision to autonomous systems and predictive analytics, continually transforming industries and enhancing human capabilities.