On condition that machine learning will make up the overwhelming majority of software development and that non-technical people might be exposed to AI systems increasingly, considered one of the foremost challenges of AI is adapting and enhancing worker skills. It’s also becoming obligatory to support teaching staff in proactively taking AI’s ethical and demanding issues under consideration.
As an open-source company democratizing machine learning, Hugging Face believes it is important to teach people from all backgrounds worldwide.
We launched the ML demo.cratization tour in March 2022, where experts from Hugging Face taught hands-on classes on Constructing Machine Learning Collaboratively to greater than 1000 students from 16 countries. Our recent goal: to show machine learning to five million people by the top of 2023.
This blog post provides a high-level description of how we’ll reach our goals around education.
🤗 Education for All
🗣️ Our goal is to make the potential and limitations of machine learning comprehensible to everyone. We imagine that doing so will help evolve the sector in a direction where the applying of those technologies will result in net advantages for society as an entire.
Some examples of our existing efforts:
- we describe in a really accessible way different uses of ML models (summarization, text generation, object detection…),
- we allow everyone to check out models directly of their browser through widgets within the model pages, hence lowering the necessity for technical skills to accomplish that (example),
- we document and warn about harmful biases identified in systems (like GPT-2).
- we offer tools to create open-source ML apps that allow anyone to grasp the potential of ML in a single click.
🤗 Education for Beginners
🗣️ We would like to lower the barrier to becoming a machine learning engineer by providing online courses, hands-on workshops, and other modern techniques.
- We offer a free course about natural language processing (NLP) and more domains (soon) using free tools and libraries from the Hugging Face ecosystem. It’s completely free and without ads. The final word goal of this course is to learn the best way to apply Transformers to (almost) any machine learning problem!
- We offer a free course about Deep Reinforcement Learning. On this course, you may study Deep Reinforcement Learning in theory and practice, learn to make use of famous Deep RL libraries, train agents in unique environments, publish your trained agents in a single line of code to the Hugging Face Hub, and more!
- We offer a free course on the best way to construct interactive demos in your machine learning models. The final word goal of this course is to permit ML developers to simply present their work to a large audience including non-technical teams or customers, researchers to more easily reproduce machine learning models and behavior, end users to more easily discover and debug failure points of models, and more!
- Experts at Hugging Face wrote a book on Transformers and their applications to a big selection of NLP tasks.
Aside from those efforts, many team members are involved in other educational efforts resembling:
- Participating in meetups, conferences and workshops.
- Creating podcasts, YouTube videos, and blog posts.
- Organizing events wherein free GPUs are provided for anyone to give you the option to coach and share models and create demos for them.
🤗 Education for Instructors
🗣️ We would like to empower educators with tools and offer collaborative spaces where students can construct machine learning using open-source technologies and state-of-the-art machine learning models.
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We offer to educators free infrastructure and resources to quickly introduce real-world applications of ML to theirs students and make learning more fun and interesting. By making a classroom free of charge from the hub, instructors can turn their classes into collaborative environments where students can learn and construct ML-powered applications using free open-source technologies and state-of-the-art models.
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We’ve assembled a free toolkit translated to eight languages that instructors of machine learning or Data Science can use to simply prepare labs, homework, or classes. The content is self-contained in order that it could be easily incorporated into an existing curriculum. This content is free and uses well-known Open Source technologies (🤗 transformers, gradio, etc). Be happy to choose a tutorial and teach it!
1️⃣ A Tour through the Hugging Face Hub
2️⃣ Construct and Host Machine Learning Demos with Gradio & Hugging Face
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We’re organizing a dedicated, free workshop (June 6) on the best way to teach our instructional resources in your machine learning and data science classes. Don’t hesitate to register.
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We’re currently doing a worldwide tour in collaboration with university instructors to show greater than 10000 students considered one of our core topics: Learn how to construct machine learning collaboratively? You’ll be able to request someone on the Hugging Face team to run the session in your class via the ML demo.cratization tour initiative.
🤗 Education Events & News
- 09/08[EVENT]: ML Demo.cratization tour in Argentina at 2pm (GMT-3). Link here
🔥 We’re currently working on more content within the course, and more! Stay tuned!
