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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 2: Lesson 2: 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 You will learn more about image classification, covering several core deep learning concepts that are necessary to get good performance: what a learning rate is and how to choose a good one, how to vary your learning rate over time, how to improve your model with data augmentation (including test-time augmentation). We also share practical tips (such as training on smaller images), an 8-step process to train a world-class image classifier, and more information on your hardware setup (including crestle, paperspace, and AWS as options).

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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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