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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 3: Lesson 3: 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 We explain convolutional networks from several different angles: the theory, a video visualization, and an Excel demo. You’ll see how to use deep learning for structured/tabular data, such as time-series sales data. We also teach a couple of key bits of math that you really need for deep learning: exponentiation and the logarithm. You will learn how to download data to your deep learning server, how to submit to a Kaggle competition, and key differences between PyTorch and Keras/TensorFlow.

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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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