A long time ago I coded up a feature for SocialCoder which converts a link - any link - to a short URL. I use it all the time for sharing links to volunteer profiles and to volunteer opportunity listings.
A new opportunity listing is posted by a charity.
I review and publish it, tweet about it, then click a button to send the charity an emailed notification of next steps.
Could it be a mail provider problem? Unlikely.
Maybe a bug, an infinite loop or recursion in my code? More likely.
I changed the notification email address so that it would only spam me, and not the charity.
But now that it was just me being spammed, and not the charity rep, I was able to calm down enough to see what had happened.
You could say it was a learning moment. So what did I learn?
Don't use HTTP GET when a POST is more appropriate. If the request parameters were in the body of the request, and not in the URL, the link would have been fine to share.
The feature that sends email should not have been available to anonymous users.
In coding terms, the controller action was missing an [Authorize] attribute. yeah ...oops.
Although the consequences of this mistake were relatively minor, affecting only me and the charity rep's Inbox, I still needed to calm down before I could see the problem clearly enough to effectively trouble-shoot. Maybe I'm drinking too much coffee. Maybe.
Being able to code a fix, run unit tests, and deploy that fix, all within within minutes is such a valuable thing.
Thank you to the @Azure team who made this so easy.
More from Tech
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/
1) During the past year, most of the anger at Facebook has been directed at Mark Zuckerberg. The question now is whether Sheryl Sandberg, the executive charged with solving Facebook’s hardest problems, has caused a few too many of her own. 2/ https://t.co/DTsc3g0hQf
2) One of the juiciest sentences in @nytimes’ piece involves a research group called Definers Public Affairs, which Facebook hired to look into the funding of the company’s opposition. What other tech company was paying Definers to smear Apple? 3/ https://t.co/DTsc3g0hQf
3) The leadership of the Democratic Party has, generally, supported Facebook over the years. But as public opinion turns against the company, prominent Democrats have started to turn, too. What will that relationship look like now? 4/
4) According to the @nytimes, Facebook worked to paint its critics as anti-Semitic, while simultaneously working to spread the idea that George Soros was supporting its critics—a classic tactic of anti-Semitic conspiracy theorists. What exactly were they trying to do there? 5/
1) During the past year, most of the anger at Facebook has been directed at Mark Zuckerberg. The question now is whether Sheryl Sandberg, the executive charged with solving Facebook’s hardest problems, has caused a few too many of her own. 2/ https://t.co/DTsc3g0hQf
2) One of the juiciest sentences in @nytimes’ piece involves a research group called Definers Public Affairs, which Facebook hired to look into the funding of the company’s opposition. What other tech company was paying Definers to smear Apple? 3/ https://t.co/DTsc3g0hQf
3) The leadership of the Democratic Party has, generally, supported Facebook over the years. But as public opinion turns against the company, prominent Democrats have started to turn, too. What will that relationship look like now? 4/
4) According to the @nytimes, Facebook worked to paint its critics as anti-Semitic, while simultaneously working to spread the idea that George Soros was supporting its critics—a classic tactic of anti-Semitic conspiracy theorists. What exactly were they trying to do there? 5/
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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My top 10 tweets of the year
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A thread 👇
https://t.co/xj4js6shhy
Entrepreneur\u2019s mind.
— James Clear (@JamesClear) August 22, 2020
Athlete\u2019s body.
Artist\u2019s soul.
https://t.co/b81zoW6u1d
When you choose who to follow on Twitter, you are choosing your future thoughts.
— James Clear (@JamesClear) October 3, 2020
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Working on a problem reduces the fear of it.
— James Clear (@JamesClear) August 30, 2020
It\u2019s hard to fear a problem when you are making progress on it\u2014even if progress is imperfect and slow.
Action relieves anxiety.
https://t.co/A7XCU5fC2m
We often avoid taking action because we think "I need to learn more," but the best way to learn is often by taking action.
— James Clear (@JamesClear) September 23, 2020
