In this course, you will :
- Learn by completing 26 advanced computer vision projects including Emotion, Age & Gender Classification, London Underground Sign Detection, Monkey Breed, Flowers, Fruits , Simpsons Characters and many more!.
- Advanced Deep Learning Computer Vision Techniques such as Transfer Learning and using pre-trained models (VGG, MobileNet, InceptionV3, ResNet50) on ImageNet and re-create popular CNNs such as AlexNet, LeNet, VGG and U-Net..
- Understand how Neural Networks, Convolutional Neural Networks, R-CNNs , SSDs, YOLO & GANs with my easy to follow explanations.
- Become familiar with other frameworks (PyTorch, Caffe, MXNET, CV APIs), Cloud GPUs and get an overview of the Computer Vision World.
- How to use the Python library Keras to build complex Deep Learning Networks (using Tensorflow backend).
- How to do Neural Style Transfer, DeepDream and use GANs to Age Faces up to 60+.
- How to create, label, annotate, train your own Image Datasets, perfect for University Projects and Startups.
- How to use OpenCV with a FREE Optional course with almost 4 hours of video.
- How to use CNNs like U-Net to perform Image Segmentation which is extremely useful in Medical Imaging application.
- How to use TensorFlow's Object Detection API and Create A Custom Object Detector in YOLO.
- Facial Recognition with VGGFace.
- Use Cloud GPUs on PaperSpace for 100X Speed Increase vs CPU.
- Build a Computer Vision API and Web App and host it on AWS using an EC2 Instance.