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Neural Networks for Machine Learning

Course Summary

Learn about artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. We'll emphasize both the basic algorithms and the practical tricks needed to get them to work well.


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    Recommended Background

    Programming proficiency in Matlab, Octave or Python. Enough knowledge of calculus to be able to differentiate simple functions. Enough knowledge of linear algebra to understand simple equations involving vectors and matrices. Enough knowledge of probability theory to understand what a probability density is.

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    Course Format

    The class will consist of lecture videos, which are between 5 and 15 minutes in length. These contain 1-3 integrated quiz questions per video. There will also be standalone homework that is not part of video lectures, optional programming assignments, and a (not optional) final test.


Course Fee:
Free

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

This course is listed under Open Source , Development & Implementations and Data & Information Management Community

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