Introduction to the Course
Get an overview of the course in this lesson.
We'll cover the following
Welcome to the course! Hugging Face is a popular deep learning model library. Even without much knowledge of convoluted concepts in modern Artificial Intelligence, Hugging Face enables us to leverage its power by inferring its models. Here's how Hugging Face introduces itself:
We're on a journey to advance and democratize NLP for everyone.
Intended audience
This course is useful for anyone who wants to use state-of-the-art machine learning (ML) models, especially Natural language processing (NLP) and computer vision models for inference. It caters to a broad spectrum of users who are working as industry engineers, software developers, data scientists, and even machine learning researchers. They can use it to perform direct inference or as an input to some other machine learning pipeline.
Prerequisites
This course doesn’t require much existing knowledge about the domain. However, we do expect you to have fundamental knowledge of the following:
- Some hands-on experience with Python.
- Familiarity with deep learning and relevant libraries is appreciated but not required. Please note that you can still perform some of the tasks without any background in deep learning, but it’ll come in handy at some stage.
Why take this course?
If you've come across this course, you're likely already aware of the growing popularity of Hugging Face. This course will provide some background on transformers
Tips on succeeding
Here are a few tips to ensure you have a great time in this course:
- Make a proper schedule and set some timelines for completing the course.
- Try to switch across both focused and diffused modes. We highly recommend the Pomodoro technique when going through a new topic.
- Try to explore the notebooks and play around with some examples relevant to your areas of interest.
Best of luck with the course. Happy learning and Carpe Diem!