The 2021 edition of the State of AI Report came out last week. So did the Kaggle State of Machine Learning and Data Science Survey. There’s much to be learned and discussed in these reports, and a couple of takeaways caught my attention.

There’s no denying that Machine Learning-powered applications…

In this video, I use AutoNLP, an AutoML product designed by Hugging Face, to train a model that classifies song lyrics according to their genre.

Then, I use Spaces to build and deploy a test web page, where I paste some lyrics and predict them.

The page is public and you can try it for yourself :)

Dataset and preprocessing notebook:

Spaces page:

Very happy to hold a paper copy of “Learn Amazon SageMaker, 2nd edition”. 532 pages and 60+ notebooks, taking you from installation to production. Available for pre-order on Amazon, Packt and everywhere else.

Table of contents:

In this video, I start from a movie review dataset and build sentiment analysis models with AutoNLP, an AutoML product designed by Hugging Face. I then predict with the best model on the Hugging Face website and in a Google Colab notebook.

In part 2, you’ll see how to quickly build a small web app with Spaces to test and demo your model.

I’m very happy to announce that the second edition of “Learn Amazon SageMaker” is now available for pre-order on Amazon (US, India, UK, France, Japan, etc.) and elsewhere. Lots of updates and additions on data preparation, bias and explainability, automation, and much more!

This book is for software engineers, machine…

In this episode, we’ll dive into SageMaker AutoPilot, an AutoML capability. Starting from a tabular dataset, we’ll launch an AutoML job in just a few clicks (or just a few lines of code).

Then, we’ll explore in detail the different steps in AutoPilot, such as automatic feature engineering and model…

In the first section, we have a chat with our special guest Greg Coquillo, a Technology Risk Manager working for Amazon. We walk through an automation project that he’s currently working on for a B2B customer operating in chemicals. In order to build material safety data sheets, the project automatically…

In this video, I show you how to use Savings Plans for Amazon SageMaker, a new cost optimization capability that helps you save up to 64% on your SageMaker workloads!

Companion blog post:

In this episode, we use state of the art models for natural language processing available in the Hugging Face collection. Then, we fine-tune BERT on a sentiment analysis dataset, and predict with the model. Finally, we show you how to scale your training jobs with data parallelism and model parallelism.

Julien Simon

Chief Evangelist, Hugging Face (

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