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It’s Christmas Time – Your Best Resources About Machine Learning for Holiday Season!

There are two types of people – those who like Christmas and indulge in the Holiday fever, and those who’d rather fly away to a deserted island to wait this time over.

And we’ve got great news for you! No matter which type of person you are, you’ll find something for yourself in this article!

So Christmas is a specific time. And as it turns out, it’s celebrated also in the world of Machine Learning. For this special occasion to help you stay on top of … trends, we’ve put together a list of the best resources for your Holiday reading list.

Check it out, enjoy, and learn!

The best resources for Christmas

🎅 We tried teaching an AI to write Christmas movie plots. Hilarity ensued. Eventually. by Karen Hao on MIT Technology Review

Using a neural network to create ridiculous plot lines takes a lot of work—and reveals the challenges of generating human language. Make sure to check it out and see the hilarious outcomes!

🎅 Reddit will never disappoint you! If you’re looking for books on ML to gift to a data scientist in your family, friends, or want to get something for yourself, you may find something of interest in this Reddit thread: Christmas gifts: books on ML.

🎅 Even though it’s from last year, this Machine Learning Christmas has daily content, articles and podcasts for all 24 days of the pre-christmas season. Everything about ML!

Perfect for fans of Advent calendars!

🎅 Here’s a KDnuggets cartoon that looks at how AI and the new technology can transform Christmas 😉

🎅 Google’s Santa Claus Tracker

As every year since 2004, you can track Santa Claus journey through the world with Google’s Santa Claus Tracker. It’s based on AI and has a suite of games and lesson plans about coding basics and Christmas traditions around the world.

It’s a great way to spend time with your family, especially kids, relax, and learn new things.

🎅 A Neural Network Wrote A Christmas Carol That Will Haunt Your Dreams on digg

Machine learning is widely used to generate songs. So why not let it write and sing a Christmas song?

Researchers at the University of Toronto trained a neural network to write a new Christmas song, and the result is… not great. Just listen for yourself!

🎅 Synthesia is an innovative content creation tool that allows you to create your own AI video. There’s also an AI Santa Claus that lets you generate personalized wishes to a friend, loved one, or even your boss.

Here are our wishes to you!

🎅 All I Want for Christmas Is AI: Write the Next Christmas Hit Using LSTMs by Tommaso Buonocore on Towards Data Science

So let’s come back to the topic of creating Christmas songs. Have you ever dreamed of creating your own Xmas carol? Yes, you can do it, with AI of course 😉

This is a nice guide that will help you create a Christmas song with machine learning. It’s helpful for all the enthusiasts of AI-generated texts, and a nice explanation on the example of Christmas songs.

At the same time, it’s an interesting read that shows how very complex networks can be designed to better address the problem of text generation.

🎅 Deep Autoencoder Neural Networks for Maximal Christmas Decoration Enjoyment by Michael C Johnson on Uncertainty…Minimized

Do you like Christmas decorations and all the bright lights? Then you’ll love this one! The author describes in this well-written piece how he embarked on a mission to create his own Christmas Light Show. Flickering lights and songs with the help of Neural Networks.

It’s a nice experiment you can do at home, so make sure to check it out!

🎅 Even Santa needs Big Data!

🎅 The Ultimate Artificial Intelligence Christmas Gift Ideas List by Tim Gülke

If you’re still looking for cool ideas for Christmas gifts, this list may help you. You’ll find something for avid practitioners of ML, the beginner, project manager, student, girlfriend, boyfriend – for everyone!

🎅 The 12 days of Machine Learning tips for creating labelled training data on SciBite

12 top tips for creating labelled Machine Learning training data. Simple but effective. It’ll help you create better models for you experiments.

🎅 A Christmas menu dreamed up by a robot by Richard Gray on BBC

Christmas means a looooot of food. So what about all the leftovers? It’s not good to throw them away. So why not ask AI for help!

A number of research teams around the world have been developing AI systems that are capable of learning from existing recipes and then coming up with some of their own. The editors asked researchers behind two innovative algorithms to see what their AI’s take would be on Christmas food.

What’s the result? Is it tasty? Check for yourself!

🎅 What would happen, if Santa Claus used ML to gift people, it’s better not to know 😉

Happy ML Christmas!

Whether you’re spending this Holiday season training your ML models or reading about AI, don’t forget to take a break and spend some quality time with friends and family to get a little human interaction 😉

Have yourself a very machine learning Christmas!


ML Experiment Tracking: What It Is, Why It Matters, and How to Implement It

10 mins read | Author Jakub Czakon | Updated July 14th, 2021

Let me share a story that I’ve heard too many times.

”… We were developing an ML model with my team, we ran a lot of experiments and got promising results…

…unfortunately, we couldn’t tell exactly what performed best because we forgot to save some model parameters and dataset versions…

…after a few weeks, we weren’t even sure what we have actually tried and we needed to re-run pretty much everything”

– unfortunate ML researcher.

And the truth is, when you develop ML models you will run a lot of experiments.

Those experiments may:

  • use different models and model hyperparameters
  • use different training or evaluation data, 
  • run different code (including this small change that you wanted to test quickly)
  • run the same code in a different environment (not knowing which PyTorch or Tensorflow version was installed)

And as a result, they can produce completely different evaluation metrics. 

Keeping track of all that information can very quickly become really hard. Especially if you want to organize and compare those experiments and feel confident that you know which setup produced the best result.  

This is where ML experiment tracking comes in. 

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