Practical Computer Vision Bootcamp -

Practical Computer Vision Bootcamp

A comprehensive, free and open-source computer vision learning path from foundational concepts to advanced applications. This hands-on bootcamp is designed for learners at various skill levels, from beginners to practitioners, focusing on practical implementation through Jupyter notebooks and real-world applications.

About this Course

This bootcamp provides a structured learning experience in computer vision, combining theoretical understanding with practical implementation. All materials are freely available on GitHub, making cutting-edge computer vision education accessible to everyone.

Course Highlights:

100% Free and Open Source - All materials available on GitHub
Interactive Jupyter notebooks with hands-on exercises
Multiple platform support (Google Colab, Kaggle)
Accompanying YouTube video series
Community Discord channel for support
Related to workshops from the Berlin Computer Vision Group

Learning Modules

1. Foundations

Digital image representation and processing
Basic image manipulation techniques
Understanding pixel data and image formats

2. Neural Network Fundamentals

Multilayer Perceptron (MLP) for image-based regression
Matrix multiplication and network architecture
Understanding neural network mechanics

3. Convolutional Neural Networks (CNNs)

LeNet5 implementation from scratch
Digit recognition projects
Dropout visualization and regularization techniques

4. Advanced Classification & Transfer Learning

Pet breed classification using real-world datasets
Pretrained ResNet models and fine-tuning
Multilabel classification techniques
Model interpretability and visualization methods

5. Image Embeddings & Similarity

Understanding high-dimensional image representations
Visualization techniques for embeddings
Clustering and organizing image datasets

6. Specialized Advanced Topics

Image Segmentation using U-Net architecture
Zero-Shot Learning with CLIP models
Generative Models including Diffusion and Stable Diffusion

Technology Stack

PyTorch - Primary deep learning framework
FiftyOne - Dataset visualization and management
TensorBoard - Training monitoring and visualization
scikit-learn - Traditional machine learning tools
Jupyter Notebooks - Interactive learning environment

Learning Resources

Interactive Notebooks with complete implementations
Video Tutorials explaining key concepts
Review Questions to reinforce learning
Community Support through Discord channel
Structured Course available on openHPI platform

Berlin Computer Vision Group Connection

This bootcamp is closely related to workshops conducted by the Berlin Computer Vision Group, a vibrant community of computer vision practitioners, researchers, and enthusiasts in Berlin. The group regularly hosts meetups, workshops, and networking events focused on the latest developments in computer vision and machine learning.

Course Features

Hands-on Learning with real-world projects
Progressive Difficulty from basics to advanced topics
Open Source Commitment - freely available to all
Community Driven with active support channels
Industry Relevant techniques and applications
Multiple Learning Formats - notebooks, videos, and interactive sessions

Get Started

Ready to dive into practical computer vision? This course is completely free and open source.

GitHub Repository: https://github.com/andandandand/practical-computer-vision
Berlin Computer Vision Group: https://www.meetup.com/de-DE/berlin-computer-vision-group/