Deep Learning
Deep Learning for Computer Vision — Learn to build and apply deep learning models like Convolutional Neural Networks (CNNs) for tasks such as image classification, object detection, and image generation using frameworks like TensorFlow and PyTorch.
Deep Learning for Computer Vision
Build and train convolutional neural networks for image classification using Keras and TensorFlow in R, starting from foundational concepts to practical models.
Deep Learning for Computer Vision
Learn how autonomous vehicles perceive the world by applying computer vision, machine learning, and sensor simulation using Python.
Deep Learning for Computer Vision
Learn to build and deploy a computer vision model as an interactive web application using Python, TensorFlow, and OpenCV.
Deep Learning for Computer Vision
Master CNNs using Python and TensorFlow to build powerful image classification and text analysis models for real-world data science applications.
Deep Learning for Computer Vision
Build practical models for object detection, neural style transfer, and image generation using Python, Keras, and TensorFlow.
Deep Learning for Computer Vision
Apply computer vision and neural networks to program a simulated autonomous vehicle using Python, TensorFlow, and OpenCV.
Deep Learning for Computer Vision
Build and train your first Convolutional Neural Network from scratch in Python to classify images using the classic CIFAR-10 dataset.
Deep Learning for Computer Vision
Master object detection and image classification by applying transfer learning and modern neural network architectures using Python and TensorFlow.
Deep Learning for Computer Vision
Master the fundamentals of image recognition and object detection by implementing CNNs, YOLO, and GANs using modern Python frameworks.
Deep Learning for Computer Vision
Build and deploy a deep learning classifier to detect face masks in real-time images and video streams using TensorFlow, Keras, and OpenCV.
Deep Learning for Computer Vision
Build and deploy image classification, object detection, and segmentation models from scratch using modern deep learning frameworks.
Deep Learning for Computer Vision
Learn to train, evaluate, and deploy custom YOLO models for object detection, instance segmentation, and pose estimation using modern computer vision pipelines.
Deep Learning for Computer Vision
Master the basics of image processing and neural networks to build your own intelligent computer vision applications on the Raspberry Pi.
Deep Learning for Computer Vision
Build automated text recognition systems for images and video using Tesseract, EasyOCR, and custom neural networks.
Deep Learning for Computer Vision
Learn to build a deep learning computer vision pipeline, extract text with OCR, and deploy your model as a functional web application using Python.
Deep Learning for Computer Vision
Master the foundations of object detection by training and evaluating Faster R-CNN, SSD, and YOLO models using TensorFlow 2 and cloud-based acceleration.
Deep Learning for Computer Vision
Build and deploy deep learning models for image classification, object detection, and segmentation using Python and PyTorch.
Deep Learning for Computer Vision
Learn to integrate deep-learning computer vision into your applications to detect objects, analyze faces, and moderate content.
Deep Learning for Computer Vision
Learn to build custom computer vision systems by mastering the full workflow from data annotation and training to real-world inference with PyTorch.
Deep Learning for Computer Vision
Learn to build, train, and deploy semantic image segmentation models using Python and PyTorch, from classic UNet architectures to modern foundation models.
Deep Learning for Computer Vision
Learn to generate thousands of labeled images automatically for computer vision projects using Python and synthetic data techniques.
Deep Learning for Computer Vision
Learn the principles of Neural Radiance Fields to generate novel 3D views and reconstruct scenes from a collection of 2D images.
Deep Learning for Computer Vision
Build and deploy deep learning models for medical image classification using Python, Keras, and proven transfer learning architectures.
Deep Learning for Computer Vision
Build, train, and deploy custom computer vision models using PyTorch, YOLO11, and Detectron2 through step-by-step written explanations and code examples.
Showing 24 of 131 courses