Practical Deep Learning For Coders
Other, , Prof. Jeremy Howard
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Updated On 02 Feb, 19
Learn how to build state of the art models without needing graduate-level mathbut also without dumbing anything down.
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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.
Sep 12, 2018
Excellent course helped me understand topic that i couldn't while attendinfg my college.
March 29, 2019
Great course. Thank you very much.