Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Catastrophic interference wikipedia , lookup
Ethics of artificial intelligence wikipedia , lookup
Person of Interest (TV series) wikipedia , lookup
Quantum machine learning wikipedia , lookup
Existential risk from artificial general intelligence wikipedia , lookup
Philosophy of artificial intelligence wikipedia , lookup
History of artificial intelligence wikipedia , lookup
Pattern recognition wikipedia , lookup
Machine Learning Defining Questions • The field of Machine Learning seeks to answer central question “How can we build computer systems that automatically improve with experience? and how can we build machines that solve problems?” • Question covers a broad range of learning tasks, how to data mine historical medical records to learn which future patients will respond best to which treatments, and how to build search engines that automatically customize to their user’s interests. Machine learning • Machine Learning is an area within Artificial Intelligence concerned with how a computational system can acquire knowledge and implement it by learning from its experiences and observations. • Machine learning is concerned with the development and analysis of algorithms and techniques that allow computers to "learn ”,and automatically improve a system's performance. Automatic improvement might include: (1) learning to perform a new task; (2) learning to perform a task more efficiently or effectively; or (3) learning and organizing new facts that can be used by a system that relies upon such knowledge. Types Of Learning • At a general level, there are two types of learning: inductive, and deductive. • Induction or inductive reasoning, sometimes called inductive logic, is the process of reasoning in which the premises of an argument are believed to support the conclusion but do not ensure it. • Deductive reasoning is the kind of reasoning in which the conclusion is necessitated by, or reached from, previously known facts (the premises). If the premises are true, the conclusion must be true . Machine learning • Machine learning usually refers to the changes in systems that perform tasks associated with artificial intelligence (AI). Such tasks involve recognition ,diagnosis, planning, robot control, prediction. The "changes" might be either enhancements to already performing systems or from the beginning to synthesis of new systems. Algorithm Types • There are many ways to categorize machine learning algorithms (Algorithm types) that based on the amount and type of background information provided to the algorithm. • The most important type: 1)supervised learning :where the algorithm generates a function that maps inputs to desired outputs. One standard formulation of the supervised learning task is the classification problem. • 2)unsupervised learning :which models a set of inputs: labeled examples are not available. Areas of Influence for Machine Learning • The most important areas: • Statistics: How best to use samples drawn from unknown probability distributions to help decide from which distribution some new sample is drawn? • Artificial Intelligence: How to write algorithms to acquire the knowledge humans are able to acquire, at least, as well as humans? Why Is Machine Learning Important? • Some tasks cannot be defined well, Machine Learning can help to defined it for example (recognizing people). • Relationships and correlations can be hidden within large amounts of data. Machine Learning/Data Mining may be able to find these relationships. • The amount of knowledge available about certain tasks might be too large for explicit encoding by humans (e.g., medical diagnostic). • Environments change over time Applications • Machine learning has a wide spectrum of applications including natural language processing ,search engines ,medical diagnosis ,bioinformatics and cheminformatics ,detecting credit card fraud ,stock market analysis, classifying DNA sequences ,speech and handwriting recognition ,object recognition in computer vision ,game playing and robot locomotion. Thanks For listening