12/6/2023 0 Comments Skim a round install![]() Transformers is a popular library focused on natural language processing (NLP) using transformers models. In this course, as we go deeper and deeper into the foundations of deep learning, we will also go deeper and deeper into the layers of fastai. ![]() The fastai library one of the most popular libraries for adding this higher-level functionality on top of PyTorch. PyTorch works best as a low-level foundation library, providing the basic operations for higher-level functionality. PyTorch is now the world’s fastest-growing deep learning library and is already used for most research papers at top conferences. We spent over a thousand hours testing PyTorch before deciding that we would use it for future courses, software development, and research. At fast.ai, we have written courses using most of the main deep learning and machine learning packages used today. We’ve completed hundreds of machine learning projects using dozens of different packages, and many different programming languages. In this course, you’ll be using PyTorch, fastai, Hugging Face Transformers, and Gradio. Start watching lesson 1 now! The software you will be using You can get what you need for state of the art work for free We’ve seen record-breaking results with <50 items of data Here’s a few things you absolutely don’t need to do world-class deep learning: Myth (don’t need) A lot of people assume that you need all kinds of hard-to-find stuff to get great results with deep learning, but as you’ll see in this course, those people are wrong. The only prerequisite is that you know how to code (a year of experience is enough), preferably in Python, and that you have at least followed a high school math course.ĭeep learning is a computer technique to extract and transform data–-with use cases ranging from human speech recognition to animal imagery classification–-by using multiple layers of neural networks. It doesn’t matter if you don’t come from a technical or a mathematical background (though it’s okay if you do too!) we wrote this course to make deep learning accessible to as many people as possible. He went on to achieve first place in the prestigious international RA2-DREAM Challenge competition! He developed a multistage deep learning method for scoring radiographic hand and foot joint damage in rheumatoid arthritis, taking advantage of the fastai library. For instance, Isaac Dimitrovsky told us that he had “ been playing around with ML for a couple of years without really grokking it… went through the fast.ai part 1 course late last year, and it clicked for me”. Many students have told us about how they’ve become multiple gold medal winners of international machine learning competitions, received offers from top companies, and having research papers published. Previous fast.ai courses have been studied by hundreds of thousands of students, from all walks of life, from all parts of the world. Start watching lesson 1 now! Is this course for me?
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