Time for a pulp countdown now, and today it's my top 10 digital watches of distinction!
After all, why wear a Rolex nowadays?
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A common misunderstanding about Agile and “Big Design Up Front”:
There’s nothing in the Agile Manifesto or Principles that states you should never have any idea what you’re trying to build.
You’re allowed to think about a desired outcome from the beginning.
It’s not Big Design Up Front if you do in-depth research to understand the user’s problem.
It’s not BDUF if you spend detailed time learning who needs this thing and why they need it.
It’s not BDUF if you help every team member know what success looks like.
Agile is about reducing risk.
It’s not Agile if you increase risk by starting your sprints with complete ignorance.
It’s not Agile if you don’t research.
Don’t make the mistake of shutting down critical understanding by labeling it Bg Design Up Front.
It would be a mistake to assume this research should only be done by designers and researchers.
Product management and developers also need to be out with the team, conducting the research.
Shared Understanding is the key objective
Big Design Up Front is a thing to avoid.
Defining all the functionality before coding is BDUF.
Drawing every screen and every pixel is BDUF.
Promising functionality (or delivery dates) to customers before development starts is BDUF.
These things shouldn’t happen in Agile.
There’s nothing in the Agile Manifesto or Principles that states you should never have any idea what you’re trying to build.
You’re allowed to think about a desired outcome from the beginning.
It’s not Big Design Up Front if you do in-depth research to understand the user’s problem.
It’s not BDUF if you spend detailed time learning who needs this thing and why they need it.
It’s not BDUF if you help every team member know what success looks like.
Agile is about reducing risk.
It’s not Agile if you increase risk by starting your sprints with complete ignorance.
It’s not Agile if you don’t research.
Don’t make the mistake of shutting down critical understanding by labeling it Bg Design Up Front.
It would be a mistake to assume this research should only be done by designers and researchers.
Product management and developers also need to be out with the team, conducting the research.
Shared Understanding is the key objective
I\u2019d recommend that the devs participate directly in the research.
— Jared Spool (@jmspool) November 18, 2018
If the devs go into the first sprint with a thorough understanding of the user\u2019s problems, they are far more likely to solve it well.
Big Design Up Front is a thing to avoid.
Defining all the functionality before coding is BDUF.
Drawing every screen and every pixel is BDUF.
Promising functionality (or delivery dates) to customers before development starts is BDUF.
These things shouldn’t happen in Agile.
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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A list of cool websites you might now know about
A thread 🧵
1) Learn Anything - Search tools for knowledge discovery that helps you understand any topic through the most efficient
2) Grad Speeches - Discover the best commencement speeches.
This website is made by me
3) What does the Internet Think - Find out what the internet thinks about anything
4) https://t.co/vuhT6jVItx - Send notes that will self-destruct after being read.
A thread 🧵
1) Learn Anything - Search tools for knowledge discovery that helps you understand any topic through the most efficient
2) Grad Speeches - Discover the best commencement speeches.
This website is made by me
3) What does the Internet Think - Find out what the internet thinks about anything
4) https://t.co/vuhT6jVItx - Send notes that will self-destruct after being read.
