Welcome to the Hugging Face Course.
This course has been designed to teach you
all about the Hugging Face ecosystem,
how to use the dataset and model hub
as well as all our open-source libraries.
Here is the Table of Contents.
As you can see, it's divided in three sections
which become progressively more advanced.
At this stage, the first two sections have been released.
So first, we'll teach you the basics
of how to use a Transformer model,
fine-tune it on your own data set
and share the result with the community.
So second, we'll dive deeper into our libraries
and teach you how to tackle any NLP task.
We're actively working on the last one
and hope to have it ready for you for the spring of 2022.
The first chapter requires no technical knowledge
and is a good introduction to learn
what Transformers models can do
and how it could be of use to you or your company.
The next chapters require a good knowledge of Python
and some basic knowledge of
Machine Learning and Deep Learning.
If you don't know what a training and validation set are
or what gradient decent means,
you should look at an introductory course
such as the ones published by deeplearning.ai or fast.ai.
It's also best if you have some basics
in one Deep Learning Framework, PyTorch or TensorFlow.
Each part of the material introduced in this course
has a version in both those frameworks,
so you will be able to pick the one
you are most comfortable with.
This is the team that developed this course.
I'll now let each of the speakers
introduce themselves briefly.
- Hi, my name is Matthew,
and I'm a Machine Learning Engineer at Hugging Face.
I work on the open-source team
and I'm responsible for maintaining particularly
the TensorFlow code there.
Previously, I was a Machine Learning Engineer at Parsley,
who've recently been acquired by Automatic,
and I was a postdoctoral researcher
before that at Trinity College, Dublin in Ireland
working on computational genetics and retinal disease.
- Hi, I'm Lysandre.
I'm a Machine Learning Engineer at Hugging Face
and I'm specifically part of the open-source team.
I've been at Hugging Face for a few years now
and alongside my team members,
I've been working on most of the tools
that you'll get to see in this course.
- Hi, I'm Sylvain.
I'm a Research Engineer at Hugging Face
and one of the main maintainers of the Transformers Library.
Previously, I worked at fast.ai
where I helped develop the fast.ai Library
as well as the online book.
Before that, I was a math and computer science teacher
in France.
- Hi, my name is Sasha and I'm a Researcher at Hugging Face,
working on the ethical,
environmental and social impacts of machine learning models.
Previously, I was a postdoctoral researcher at Mila,
University in Montreal
and I also worked as an Applied AI Researcher
for the United Nations Global Pulse.
I've been involved in projects such as CodeCarbon
and the Machine Learning Impacts Calculator
to measure the carbon footprint of machine learning.
- Hi, I'm Merve and I'm a Developer Advocate
at Hugging Face.
Previously, I was working as a Machine Learning Engineer
building NLP tools and chat bots.
Currently, I'm working to improve the hub
and democratize machine learning.
- Hello everyone.
My name is Lucile and I'm a Machine Learning Engineer
at Hugging Face.
To tell you in two sentences who I am,
I work on the development and support of open-source tools
and I also participate in several research project
in the field of Natural Language Processing.
- Good day there.
I'm Lewis and I'm a Machine Learning Engineer
in the open-source team at Hugging Face.
I'm passionate about developing tools for the NLP community
and you'll see me at many of Hugging Face's
outreach activities.
Before joining Hugging Face,
I spent several years developing
machine learning applications for startups
and enterprises in the domains of NLP,
topological data analysis and time series.
In a former life, I was a theoretical physicist,
where I researched particle collisions
at the Large Hadron Collider and so.
- Hey, I'm Leandro and I'm a Machine Learning Engineer
in the open-source team at Hugging Face.
Before joining Hugging Face, I worked as a Data Scientist
in Switzerland and have taught Data Science at University.