Deep Learning Track WiSe 24/25
Deep Learning Track WiSe 24/25
Deep Learning Track WiSe 24/25
  • Welcome to the Deep Learning Track
  • Setup
  • Learning Material
  • Section 1 - The Math
    • Derivatives and Gradients
    • Vectors, Matrices and Tensors
    • The power of matrix computation
    • Exercise - Matrix Computation
  • Section 2 - The Data
    • PyTorch Datasets and Data Loaders
    • Working with Data Tables
    • Exercise - Loading Data from a CSV file
    • Working with Images
    • Exercise - Image Datasets
    • Working with Text
  • Section 3 - Neural Networks
    • Activation Functions
    • Exercise - Activation Functions
    • Exercise - The Softmax Function
    • The Neuron
    • Two type of applications: Regression and Classification
    • Loss Functions
    • Exercise - Regression Loss Functions
    • Exercise - Classification Loss Functions
    • The Gradient Descent Algorithm
    • Exercise - Implementing Gradient Descent
    • Exercise - PyTorch Autograd
    • Exercise - Regression with Neural Networks
    • Exercise - Classification with Neural Networks
    • Playground - Neural Networks
  • Section 4 - Convolutional Neural Networks
    • Convolution
    • Convolutional Neural Networks
    • Classifying handwritten digits
    • Playground - Convolutional Neural Networks
    • Transfer Learning
  • Final Project - Text Classification
  • Further Resources
    • Computer Vision Libraries
    • Image Classification with PyTorch
    • Object Detection with PyTorch
    • Deep AI Explainability
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On this page
  • Ultralytics Computer Vision Models
  • Roboflow
  • Supervision
  • OpenMMLab
  1. Further Resources

Computer Vision Libraries

We have covered the basics of deep learning and computer vision in this cours. But there is still much to explore. We will show you some advanced computer vision libraries and tools here.

PreviousFurther ResourcesNextImage Classification with PyTorch

Ultralytics Computer Vision Models

Ultralytics is a company that provides a lot of state-of-the-art computer vision models like Yolo or Segment Anything. The nice thing about Ultralytics is that you can use these models freely. They also provide a nice Python API for these models that makes working with them very easy.

Roboflow

Roboflow is a website for managing datasets and training models. If you need free datasets this site provides a lot.

Supervision

Supervision is a library from Roboflow that makes drawing bounding boxes and annotating images very easy.

OpenMMLab

OpenMMLab is one of the most advances libraries for computer vision based on PyTorch. It provides a lot of predefined model architectures and an easy to use API.

Models Supported by Ultralytics
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Roboflow: Computer vision tools for developers and enterprises
Supervision
OpenMMLabGitHub
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