From the course: Deep Learning and Computer Vision: Object Detection with PyTorch
Prerequisites - PyTorch Tutorial
From the course: Deep Learning and Computer Vision: Object Detection with PyTorch
Prerequisites
- [Narrator] Before diving into this course, let's quickly go over the prerequisite skills and tools that will help you get the most out of it. To follow along, you should have a basic understanding of Python programming. If you're comfortable with variables, loops, functions, and object oriented programming, you are all set. If you need a refresher, check out courses related to Python basics, while we'll cover deep learning from the ground up, having a foundational knowledge of machine learning concepts like supervised learning, unsupervised learning, training datasets and model evaluation will be helpful. Knowledge regarding some mathematical concepts like linear algebra, including matrices and vectors will be helpful. Don't worry if you are not an expert. We'll introduce key concepts as needed. For hands-on coding, we'll use Python and PyTorch and we'll be running our code in GitHub Codespaces, a cloud-based development environment. No setup worries, just right and run code instantly. This course is perfect for software developers, AI enthusiast, data scientist, and students who want to master deep learning for computer vision. Whether you are a beginner in deep learning or looking or to level up skills, you will find value in this course. Now that you know what's needed, let's move forward. In the next video, we'll start exploring the fundamentals of deep learning. See you there.
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