On Wednesday, The New York Times published a blockbuster report on the failures of Facebook’s management team during the past three years. It's.... not flattering, to say the least. Here are six follow-up questions that merit more investigation. 1/
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THREAD: How is it possible to train a well-performing, advanced Computer Vision model 𝗼𝗻 𝘁𝗵𝗲 𝗖𝗣𝗨? 🤔
At the heart of this lies the most important technique in modern deep learning - transfer learning.
Let's analyze how it
2/ For starters, let's look at what a neural network (NN for short) does.
An NN is like a stack of pancakes, with computation flowing up when we make predictions.
How does it all work?
3/ We show an image to our model.
An image is a collection of pixels. Each pixel is just a bunch of numbers describing its color.
Here is what it might look like for a black and white image
4/ The picture goes into the layer at the bottom.
Each layer performs computation on the image, transforming it and passing it upwards.
5/ By the time the image reaches the uppermost layer, it has been transformed to the point that it now consists of two numbers only.
The outputs of a layer are called activations, and the outputs of the last layer have a special meaning... they are the predictions!
At the heart of this lies the most important technique in modern deep learning - transfer learning.
Let's analyze how it
THREAD: Can you start learning cutting-edge deep learning without specialized hardware? \U0001f916
— Radek Osmulski (@radekosmulski) February 11, 2021
In this thread, we will train an advanced Computer Vision model on a challenging dataset. \U0001f415\U0001f408 Training completes in 25 minutes on my 3yrs old Ryzen 5 CPU.
Let me show you how...
2/ For starters, let's look at what a neural network (NN for short) does.
An NN is like a stack of pancakes, with computation flowing up when we make predictions.
How does it all work?
3/ We show an image to our model.
An image is a collection of pixels. Each pixel is just a bunch of numbers describing its color.
Here is what it might look like for a black and white image
4/ The picture goes into the layer at the bottom.
Each layer performs computation on the image, transforming it and passing it upwards.
5/ By the time the image reaches the uppermost layer, it has been transformed to the point that it now consists of two numbers only.
The outputs of a layer are called activations, and the outputs of the last layer have a special meaning... they are the predictions!
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Krugman is, of course, right about this. BUT, note that universities can do a lot to revitalize declining and rural regions.
See this thing that @lymanstoneky wrote:
And see this thing that I wrote:
And see this book that @JamesFallows wrote:
And see this other thing that I wrote:
One thing I've been noticing about responses to today's column is that many people still don't get how strong the forces behind regional divergence are, and how hard to reverse 1/ https://t.co/Ft2aH1NcQt
— Paul Krugman (@paulkrugman) November 20, 2018
See this thing that @lymanstoneky wrote:
And see this thing that I wrote:
And see this book that @JamesFallows wrote:
And see this other thing that I wrote: