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Lecture 14 Expectation Maximization Algorithms | Stanford CS229 Machine Learning Autumn 2018

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Lessons List | 20 Lesson

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11 Reviews


Akanchha

Great 2023-11-17

Abira James

Videos in this course doesn't play. It refers you to watch on YouTube. So the progress bar won't show anything. Kindly fix it ASAP. 2023-10-20

Ram Babu.B

Nice 2023-10-06

Faraz Malik

when playing any video it says "Video unavailable Playback on other websites has been disabled by the video owner Watch on YouTube..... 2023-06-07

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Course Description

Machine learning Field of study Machine learning is the study of computer algorithms that improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Is machine learning hard? Why is machine learning 'hard'? ... There is no doubt the science of advancing machine learning algorithms through research is difficult. It requires creativity, experimentation and tenacity. Machine learning remains a hard problem when implementing existing algorithms and models to work well for your new application.What is the goal of machine learning? Machine Learning Defined Its goal and usage is to build new and/or leverage existing algorithms to learn from data, in order to build generalizable models that give accurate predictions, or to find patterns, particularly with new and unseen similar data.What are the basics of machine learning? Key Elements of Machine Learning Every machine learning algorithm has three components: Representation: how to represent knowledge. Examples include decision trees, sets of rules, instances, graphical models, neural networks, support vector machines, model ensembles and others.