Deep Learning Computer Vision™ CNN, OpenCV, YOLO, SSD & GANs

Free Course-You, Will, learn Deep Learning Computer Vision CNN OpenCV YOLO SSD GANs course in free and download the course free Google drive link.

Learn advanced deep learning computer vision techniques such as transfer learning and pre-training models (VGG, Mobile Net, Inception V3, ResNet 50) on imagenet and recreate popular CNNs such as AlexNet, Bennet, VGG, and U-Net.

Understand how neural networks, convolutional neural networks, R-CNNs, SSDs, YOLO & GANs can easily follow my descriptions

Get acquainted with other frameworks (Pytorch, Cafe, MXNET, CV APIs), Cloud GPUs, and get an overview of Computer Vision World
Learn how to use the Python library Keras to build complex deep learning networks (using the TensorFlow backend)

Deep Learning Computer Vision CNN OpenCV YOLO SSD GANs

Learn how to do Neural Style Transfer, DeepDream and use GANs for faces aged 60+
Learn how to create, label, annotate and train your own image datasets suitable for university projects and startups

Learn how to use OpenCV with a free optional course with almost 4 hours of video
Learn how to use CNN’s like U-Net to make image segmentation very useful in medical imaging applications
Learn how to use Tensor Flow’s Object Detection API and create a custom object detector in YOLO

Learn facial recognition with VGGFace
Learn to use cloud GPUs in paper space for 100X speed increase vs CPU
Learn how to create a Computer Vision API and web application and host it on AWS using the EC2 example

Deep Learning Computer Vision CNN OpenCV YOLO SSD GANs

Deep Learning Computer Vision CNN OpenCV YOLO SSD GANs Course Requirements

Basic programming knowledge is a plus but not required
High school level math, college-level bonus
At least 20GB of storage space for virtual machines and datasets
Windows, macOS or Linux OS

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Created by

Rajeev D. Ratan
Last updated 3/2021
English [Auto-generated]

Size: 11.08 GB

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