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Lecture 1: What is Machine Learning? Building a performing Machine Learning model from A to Z. Embed Size px. Start on. Show related SlideShares at end. WordPress Shortcode. Share Email. Top clipped slide. Machine Learning Mar. Darshan Ambhaikar Machine learning ppt slideshare download. Software Developer Intern. Machine Learning: Applications, Process and Techniques.
Introduction to machine learning and deep learning. Advantages and disadvantages of machine learning language. More Related Content Slideshows for you Machine Learning and Real-World Applications.
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Introduction Machine learning, a branch of artificial intelligence, concerns the construction and study of systems that can learn from data. Mitchell provided a widely quoted, more formal definition: “A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E” Definition Machine Learning 5.
So What Is Machine Learning? Generalization Focuses on the discovery of previously unknown properties on the data. Performance is usually evaluated with respect to the ability to reproduce known knowledge. The key task is the discovery of previously unknown knowledge.
Evaluated with respect to known knowledge This is the algorithm part of the data mining process Application of algorithms to search for patterns and relationships that may exist in large databases. Algorithms Algorithm types Machine learning algorithms can be organized based on the desired outcome of the algorithm or the type of input available machine learning ppt slideshare download training the machine 1.
Supervised learning algorithms are trained on labeled examples, i. Unsupervised learning algorithms operate on unlabelled examples, i. Semi-supervised learning combines both labeled and unlabelled examples to generate an appropriate function or classifier. Http://replace.me/19312.txt learning is concerned with how intelligent agents ought to act in an environment to maximize some notion of reward machine learning ppt slideshare download sequence of actions Other algorithms are: Learning to learn Developmental learning Transduction etc.
The process continues till we reach machine learning ppt slideshare download leaf node. Artificial neural networks 2. Inductive logic programming 3.
Support vector machines 4. Bayesian networks 5. Reinforcement learning 6. Association Rule learning 7. Clustering Other learning techniques After learning, it can then be used to classify new email messages into read and unread folders. Prediction of financial indices from textual news streams In this application news streams from 20 machine learning ppt slideshare download sources are digitized and used as the input to a neural network predictor of a financial time series High explosives detector for airport security checkpoints Oil pipeline defect recognition and quantification Machine learning ppt slideshare download performance control of iterative linear solver Applications of Machine Learning Machine perception Computer vision object recognition Natural language processing Syntactic pattern recognition Search engines Medical diagnosis Bioinformatics Brain-machine interfaces Cheminformatics Detecting credit card fraud Stock market analysis Classifying DNA sequences Sequence mining Speech and handwriting recognition Game playing Software engineering Adaptive websites Robot locomotion Computational advertising Computational finance Structural health monitoring opinion mining Affective computing Information retrieval Recommender systems Pedestrian Detection References:- 1.
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