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Practical Deep Learning For Coders

Other, , Prof. Jeremy Howard

Overview

Learn how to build state of the art models without needing graduate-level mathbut also without dumbing anything down.


This 7-week course is designed for anyone with at least a year of coding experience, and some memory of high-school math. You will start with step onelearning how to get a GPU server online suitable for deep learningand go all the way through to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems.

Includes

Lecture 6: Lesson 6: Deep Learning 2018

4.1 ( 11 )


Lecture Details

NB: Please go to http://course.fast.ai to view this video since there is important updated information there. If you have questions, use the forums at http://forums.fast.ai Today is a very busy lesson! We first learn how to interpret the collaborative filtering embeddings we created last week, and use that knowledge to answer the question: "what is the worst movie of all time?" Then we cover what is perhaps the most practically important topic in the whole course: how to use deep learning to model "structured data" such as database tables and spreadsheets, as well as time series. It turns out that not only is deep learning often the most accurate modeling approach for this tasks, it can be the easiest approach to develop too. We close out the lesson with an introduction to recurrent neural networks (RNNs), and use an RNN to write a new philosophical treatise...

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Comments
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Sam

Excellent course helped me understand topic that i couldn't while attendinfg my college.

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Dembe

Great course. Thank you very much.

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