MACHINE LEARNING UNIT : 1 INTRODUCTION SHRUTHISHREE S.H |ASST.PROF|DEPT.OF ISE | JAIN UNIVERSITY UNIT – I INTRODUCTION TO MACHINE LEARNING Introduction to Machine Learning. 1.1 Types of Learnings: 1.1.1 Supervised learning: [A]Image Classification, [B]Market Prediction/Regression,. 1.1.2 Unsupervised learning: [A] Clustering, [B] High Dimension Visualization, [C] Generative Models, 1.1.3 Semi-supervised learning, [A] Reinforcement learning, 1.2 Terminologies of Machine Learning.
MACHINE LEARNING UNIT : 1 INTRODUCTION SHRUTHISHREE S.H |ASST.PROF|DEPT.OF ISE | JAIN UNIVERSITY Introduction to Machine Learning. What is Machine Learning? “Machine learning refers to a system capable of the autonomous acquisition and integration of knowledge.” Machine learning teaches computers to do what comes naturally to humans and animals: learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. The algorithms adaptively improve their performance as the number of samples available for learning increases. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly. Machine learning algorithms find natural patterns in data that generate insight and help you make better decisions and predictions. They are used every day to make critical decisions in medical diagnosis, stock trading, energy load forecasting, and more. Media sites rely on machine learning to sift through millions of options to give you song or movie recommendations. Retailers use it to gain insight into their customers’ purchasing behavior. Learning – It is the process of converting experience into expertise or knowledge. The input to a learning algorithm is training data, representing experience, and the output is some expertise, which usually takes the form of another computer program that can perform some task. Machine Learning – Machine learning is the science of getting computers to act, to learn & improve from experience, without explicitly being programmed. If programming is automation, then, machine learning is automating the process of automation. It focuses on the development of computer programs that can access data& use it learn for themselves.
- Winter '17
- Machine Learning