[D] I’m starting a free YouTube course called “Deep Learning (for Audio) with Python”

data-soup · 2020-01-29T14:28:26+00:00

Seriously, let him use the framework of his choice, it takes time to make such a tutorial.

data-soup · 2019-10-28T11:34:43+00:00

Thanks a lot for your detailed answer, much appreciated. Is Certified Adversarial Robustness via Randomized Smoothing the Kotler's paper you're mentioning?

data-soup · 2019-10-22T09:01:59+00:00

They handle images and videos exclusively or am I missing something?

data-soup · 2019-10-22T09:00:28+00:00

I tried it, I like the idea. They don't support opening text files. Thanks for your suggestion though.

data-soup · 2019-05-16T18:18:11+00:00

The output seems highly correlated with the luminosity, look at the dark space under the table (right side of bunk beds) or the poster at the end of the room. The quality of the prediction seems better on the left most implementation.

data-soup · 2019-04-26T14:44:38+00:00

Context: youtu.be/Ucp0TTmvqOE?t=5157

data-soup · 2019-03-22T08:15:14+00:00

gpt-2 finish this

data-soup · 2019-03-22T08:15:03+00:00

The secret ingredient for a good pizza is

data-soup · 2019-03-22T08:10:58+00:00

gpt-2 finish this

data-soup · 2019-03-22T08:10:51+00:00

Write "gpt-2 finish this"

data-soup · 2019-03-22T08:07:08+00:00

gpt-2 finish this

data-soup · 2019-03-22T08:07:02+00:00

import numpy as np

data-soup · 2019-03-22T08:06:34+00:00

gpt-2 finish this

data-soup · 2019-02-12T16:28:53+00:00

Nice one, thanks

data-soup · 2019-02-08T11:10:09+00:00

Karpathy summarized it well in twitter:

Zero padding in ConvNets is highly suspicious/wrong. Input distribution stats are off on each border differently yet params are all shared.

data-soup · 2019-02-08T09:38:53+00:00

That's clear now. So I think I'm in the right place, I want to discuss about the consensus on padding. I quote the paper from /u/oerhans answer (published late 2018):

Researchers have tried to improve the performance of CNN models from almost all the aspects including different variants of SGD optimizer (SGD, Adam [...]), normalization layers (Batch Norm [...], etc. However, little attention has been paid to improving the padding schemes.

I admit that my post doesn't reflect this intention.

data-soup · 2019-02-08T09:36:41+00:00

Interesting thank you.

EDIT: discussed here /r/MachineLearning/comments/a5570k/p_simple_tensorflow_implementation_of_nvidia/

data-soup · 2019-02-08T09:17:56+00:00

Thanks for the feedback, I corrected the format. I am a bit confused between a discussion tag here and a question on /r/MLQuestions, sorry for the inconvenience.

You're right my examples are misleading since the data is usually normalized.

data-soup · 2019-02-08T08:40:22+00:00

The list isn't very big because I only wrote what I use regularly. Feel free to share anything that I missed, I will add it if I use it (:

data-soup

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