An NN is like a stack of pancakes, with computation flowing up when we make predictions.
How does it all work?
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
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...
An NN is like a stack of pancakes, with computation flowing up when we make predictions.
How does it all work?
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
Each layer performs computation on the image, transforming it and passing it upwards.
The outputs of a layer are called activations, and the outputs of the last layer have a special meaning... they are the predictions!
We would like for it to have a high value, and for other activations in the last layer to be small...
So far so good! But what about transfer learning?
We know that these layers evolve during training to become feature detectors.
What do we mean by that?
A layer above might have windows that construct shapes from these lines.
We might have a window light up when it sees a square, another when it sees a colorful blob.
Maybe one sliding window will combine lines and detect text... maybe another one will learn to detect faces.
Does all of this sound like a hard task?
But, presumably, once we detect all these lower-level features, we can combine them in a plethora of interesting ways? 🤔
Or trains, planes, and ships. Or blood cell boundaries. Or aneurysms in x-rays. The possibilities are endless!
We let researchers, large corporations, spend millions of dollars to train very complex models.
And then we get to build on top of their work! 😇
But so much for the theory. How does it all work in practice?
The @fastdotai framework downloaded the model for us and removed the top of it (the part responsible for predicting 1 of 1000 classes).
During training, we kept nearly the entire model frozen, and only trained the uppermost part, making use of all the lower level features that were being detected.
Ingenius! 😁
We will hopefully get a chance to explore all of them 🙂
If you enjoyed this thread, let me know please and help me reach others who might also be interested 😊🙏
And the visualizations of what the layers can detect?
Next stop - deciphering how it all works in code and finding ways to further improve our model!
Stay tuned for more 🙂
More from Tech
The first area to focus on is diversity. This has become a dogma in the tech world, and despite the fact that tech is one of the most meritocratic industries in the world, there are constant efforts to promote diversity at the expense of fairness, merit and competency. Examples:
USC's Interactive Media & Games Division cancels all-star panel that included top-tier game developers who were invited to share their experiences with students. Why? Because there were no women on the
ElectronConf is a conf which chooses presenters based on blind auditions; the identity, gender, and race of the speaker is not known to the selection team. The results of that merit-based approach was an all-male panel. So they cancelled the conference.
Apple's head of diversity (a black woman) got in trouble for promoting a vision of diversity that is at odds with contemporary progressive dogma. (She left the company shortly after this
Also in the name of diversity, there is unabashed discrimination against men (especially white men) in tech, in both hiring policies and in other arenas. One such example is this, a developer workshop that specifically excluded men: https://t.co/N0SkH4hR35
USC's Interactive Media & Games Division cancels all-star panel that included top-tier game developers who were invited to share their experiences with students. Why? Because there were no women on the
ElectronConf is a conf which chooses presenters based on blind auditions; the identity, gender, and race of the speaker is not known to the selection team. The results of that merit-based approach was an all-male panel. So they cancelled the conference.
Apple's head of diversity (a black woman) got in trouble for promoting a vision of diversity that is at odds with contemporary progressive dogma. (She left the company shortly after this
Also in the name of diversity, there is unabashed discrimination against men (especially white men) in tech, in both hiring policies and in other arenas. One such example is this, a developer workshop that specifically excluded men: https://t.co/N0SkH4hR35
Here is a simple example of a machine learning model.
I put it together a long time ago, and it was very helpful! I sliced it apart a thousand times until things started to make sense.
It's TensorFlow and Keras.
If you are starting out, this may be a good puzzle to solve.
The goal of this model is to learn to multiply one-digit
I put it together a long time ago, and it was very helpful! I sliced it apart a thousand times until things started to make sense.
It's TensorFlow and Keras.
If you are starting out, this may be a good puzzle to solve.
The goal of this model is to learn to multiply one-digit
It is a good example of coding, what is the model?
— Freddy Rojas Cama (@freddyrojascama) February 1, 2021
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https://t.co/FBfXhUrH5d
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Oh my Goodness!!!
I might have a panic attack due to excitement!!
Read this thread to the end...I just had an epiphany and my mind is blown. Actually, more than blown. More like OBLITERATED! This is the thing! This is the thing that will blow the entire thing out of the water!
Has this man been concealing his true identity?
Is this man a supposed 'dead' Seal Team Six soldier?
Witness protection to be kept safe until the right moment when all will be revealed?!
Who ELSE is alive that may have faked their death/gone into witness protection?
Were "golden tickets" inside the envelopes??
Are these "golden tickets" going to lead to their ultimate undoing?
Review crumbs on the board re: 'gold'.
#SEALTeam6 Trump re-tweeted this.
I might have a panic attack due to excitement!!
Read this thread to the end...I just had an epiphany and my mind is blown. Actually, more than blown. More like OBLITERATED! This is the thing! This is the thing that will blow the entire thing out of the water!
Tik Tok pic.twitter.com/8X3oMxvncP
— Scotty Mar10 (@Allenma15086871) December 29, 2020
Has this man been concealing his true identity?
Is this man a supposed 'dead' Seal Team Six soldier?
Witness protection to be kept safe until the right moment when all will be revealed?!
Who ELSE is alive that may have faked their death/gone into witness protection?
Were "golden tickets" inside the envelopes??
Are these "golden tickets" going to lead to their ultimate undoing?
Review crumbs on the board re: 'gold'.
#SEALTeam6 Trump re-tweeted this.
Margatha Natarajar murthi - Uthirakosamangai temple near Ramanathapuram,TN
#ArudraDarisanam
Unique Natarajar made of emerlad is abt 6 feet tall.
It is always covered with sandal paste.Only on Thriuvadhirai Star in month Margazhi-Nataraja can be worshipped without sandal paste.
After removing the sandal paste,day long rituals & various abhishekam will be https://t.co/e1Ye8DrNWb day Maragatha Nataraja sannandhi will be closed after anointing the murthi with fresh sandal paste.Maragatha Natarajar is covered with sandal paste throughout the year
as Emerald has scientific property of its molecules getting disturbed when exposed to light/water/sound.This is an ancient Shiva temple considered to be 3000 years old -believed to be where Bhagwan Shiva gave Veda gyaana to Parvati Devi.This temple has some stunning sculptures.
#ArudraDarisanam
Unique Natarajar made of emerlad is abt 6 feet tall.
It is always covered with sandal paste.Only on Thriuvadhirai Star in month Margazhi-Nataraja can be worshipped without sandal paste.
After removing the sandal paste,day long rituals & various abhishekam will be https://t.co/e1Ye8DrNWb day Maragatha Nataraja sannandhi will be closed after anointing the murthi with fresh sandal paste.Maragatha Natarajar is covered with sandal paste throughout the year
as Emerald has scientific property of its molecules getting disturbed when exposed to light/water/sound.This is an ancient Shiva temple considered to be 3000 years old -believed to be where Bhagwan Shiva gave Veda gyaana to Parvati Devi.This temple has some stunning sculptures.
