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FreeHugging Face Community Computer Vision Course
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This is a community-driven course that covers computer vision from fundamentals through recent models. Theory sections are paired with tutorials that run in Google Colab notebooks, so you train and apply models as you go.
The 13 units move from basic principles and convolutional networks through vision transformers, multimodal and generative models, and on to video, 3D reconstruction, model optimization and synthetic data. The later units cover zero-shot methods, ethics and biases, and emerging trends.
Some Python and familiarity with transformers, machine learning and neural networks are expected. If those are new to you, the first unit of the Hugging Face NLP course is suggested as preparation.
Welcome to the community-driven course on computer vision. Computer vision is revolutionizing our world in many ways, from unlocking phones with facial recognition to analyzing medical images for disease detection, monitoring wildlife, and creating new images. Together, we’ll dive into the fascinating world of computer vision!
Throughout this course, we’ll cover everything from the basics to the latest advancements in computer vision. It’s structured to include various foundational topics, making it friendly and accessible for everyone. We’re delighted to have you join us for this exciting journey!
What you will learn
The course is composed of theory, practical tutorials, and engaging challenges.
Course Structure
The course is organized into multiple units, covering the fundamentals and delving into an in-depth exploration of state-of-the-art models.
Pre-requisites
Before beginning this course, make sure that you have some experience with Python programming and are familiar with transformers, machine learning, and neural networks. If these are new to you, consider reviewing the first unit of the Hugging Face NLP course. While a strong knowledge of pre-processing techniques and mathematical operations like convolutions is beneficial, they are not prerequisites.
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