Engineering Applications using Machine Learning
Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. It is seen as a part of artificial intilligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.
A subset of machine learning is closely related to computational statitics, which focuses on making predictions using computers; but not all machine learning is statistical learning. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a related field of study, focusing on exploratory data analysis through unsupervised. Some implementations of machine learning use data and neural networks in a way that mimics the working of a biological brain. In its application across business problems, machine learning is also referred to as predictive analytics.
Related Conference of Engineering Applications using Machine Learning
9th International Meeting on Fluid Dynamics & Fluid Mechanics
13th World Congress on Physical and Theoretical Chemistry
8th World Congress on Emerging Trends in Science, Engineering and Technology
9th International Conference on Astronomy, Astrophysics and Space Science
Engineering Applications using Machine Learning Conference Speakers
Recommended Sessions
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- Data Science
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