Check out these amazing machine learning challenges
By: Mark Farragher
Tags: Artificial Intelligence, Machine Learning, Deep Learning

Hey, pssst!

Want to earn a quick $25,000?

All you need to do is train a deep neural network to recognize all ships in a satellite photo like this one:

Airbus wants to build a high-speed shipping monitoring service. They will pay anyone $25,000 who can come up with the most accurate ship detection algorithm. And there’s another $25,000 bonus prize for the fastest algorithm.

Check out the competition here: https://www.kaggle.com/c/airbus-ship-detection#des…

Doesn’t look too hard, does it?

You might be able to pull it off with an off-the-shelf Convolutional Neural Network re-trained on shipping images.

Okay, but what if there’s a haze or cloud cover blocking a clear view of the ships?

Can you crack this problem?

Here’s another challenge:

Check out this news snippet from Western Digital’s third quarter earnings call, when CEO Steven Milligan said:

“… And when we’re looking at a normalizing environment, that means that we’re going to kind of more normal, more consistent ASP declines like we’ve seen historically in a controlled environment. So, you’re basically seeing the margin percentage drift down a bit, but in a very measured way. And so we’re seeing a bit of that. We’re not alarmed by it. It’s still a great environment for us. And so that’s really what we mean by normalizing… “

Looks innocent, doesn’t it?

Think again. After this message, shareholders panicked and sold their shares en masse.

The stock fell 8%.

Turns out the word ‘normalizing’ in the semiconductor business is code for: supply has caught up with demand and profits are about to drop.

Enter Two Sigma, a stock analysis company, which is offering a $25,000 prize for anyone who can build a neural network that can predict stock movements from news articles. There are more prizes for 2nd to 7th place, the total prize pot is $100,000.

Check out the competition here: https://www.kaggle.com/c/two-sigma-financial-news#…

You could take Google’s famous BERT network, which is specifically designed for Natural Language Processing, and teach it that semiconductor businesses tend to crash when the word ‘normalizing’ starts showing up in news articles.

Will you design the winning algorithm?

Okay, last one! This one is a classic.

Check out the following image:

That’s a chest x-ray. But now for the million dollar question:

Does this patient have pneumonia or not?

Pneumonia is no laughing matter. More than 900,000 children under the age of 5 die each year from pneumonia. So being able to detect the disease as early as possible is super important.

The Radiological Society of North America has awarded a $12,000 cash prize for any algorithm that can detect pneumonia early in chest x-rays. And there are more prizes for 2nd to 10th place.

Check out the competition here: https://www.kaggle.com/c/rsna-pneumonia-detection-…

Pneumonia shows up as little white blobs on x-rays. But unfortunately, a lot of other conditions also produce the same blobs. Your algorithm needs to analyze the position, shape, and opacity of the blobs to determine if the patient has pneumonia or not.

A very good start is to use a Convolutional Neural Network with lots of layers. The secret sauce is to design the correct number of layers, and the correct convolutional kernel in each layer.

Crack this problem and you are saving almost a million children per year.

Are you up for this challenge?

There are many more competitions like this. You can browse the full list here: https://www.kaggle.com/competitions

Was there any specific challenge that caught your eye?

Leave a comment and let me know!