Learn to build a complete real-time object detection system with YOLOv8 and Python. Covers custom training, optimization, and production deployment with FastAPI.
Build a real-time emotion detection system with PyTorch. Learn CNN architectures, transfer learning, data augmentation & production deployment.
Learn to build a multi-modal image captioning system using PyTorch, combining CNNs and Transformers. Includes encoder/decoder architecture, training techniques, and evaluation. Transform images to text with deep learning.
Learn to build Vision Transformers in PyTorch from scratch. Complete guide covers patch embedding, self-attention, transfer learning, and CIFAR-10 training. Start coding today!
Learn to build custom CNN architectures for multi-class image classification with PyTorch transfer learning, data augmentation, and advanced training techniques.
Learn to build a real-time object detection system using YOLOv8 and PyTorch. Complete guide covers training, optimization, and production deployment with FastAPI.
Learn to build and train custom Variational Autoencoders in PyTorch for image generation and latent space analysis. Complete tutorial with theory, implementation, and optimization techniques.
Learn to build and train a custom Vision Transformer (ViT) from scratch using PyTorch. Master patch embedding, attention mechanisms, and advanced optimization techniques for superior computer vision performance.
Learn to build custom CNN models for image classification using TensorFlow and Keras. Complete guide with code examples, training tips, and optimization strategies.
Learn to build a real-time object detection system with YOLOv8 and FastAPI in Python. Complete guide covering custom training, web deployment & optimization.
Learn to build custom CNNs for image classification using PyTorch with data augmentation and transfer learning techniques. Complete tutorial with CIFAR-10 examples and optimization tips.
Learn to build and train a Variational Autoencoder (VAE) with PyTorch for image generation. Complete tutorial covers mathematical foundations, implementation, and advanced techniques.
Learn to build a powerful multi-class image classifier using transfer learning with TensorFlow and Keras. Complete guide with code examples, data preprocessing, and model optimization techniques.