UDEMY 2021 - Deep Learning Computer Vision™ CNN, OpenCV, YOLO, SSD & GANs

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Go from beginner to Expert in using Deep Learning for Computer Vision (Keras & Python) completing 28 Real World Projects

You can find "Download Link" as a button at the end of this article.

What you’ll learn

  • 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!
  • Learn 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.
  • Learn 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
  • 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
  • Learn how to use the Python library Keras to build complex Deep Learning Networks (using Tensorflow backend)
  • Learn how to do Neural Style Transfer, DeepDream and use GANs to Age Faces up to 60+
  • Learn how to create, label, annotate, train your own Image Datasets, perfect 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 CNNs like U-Net to perform Image Segmentation which is extremely useful in Medical Imaging application
  • Learn how to use TensorFlow’s Object Detection API and Create A Custom Object Detector in YOLO
  • Learn Facial Recognition with VGGFace
  • Learn to use Cloud GPUs on PaperSpace for 100X Speed Increase vs CPU
  • Learn to Build a Computer Vision API and Web App and host it on AWS using an EC2 Instance
  • Requirements

  • Basic programming knowledge is a plus but not a requirement
  • High school level math, College level would be a bonus
  • Atleast 20GB storage space for Virtual Machine and Datasets
  • A Windows, MacOS or Linux OS
  • Description

    Deep Learning Computer Vision™ Use Python & Keras to implement CNNs, YOLO, TFOD, R-CNNs, SSDs & GANs + A Free Introduction to OpenCV3.

    If you want to learn all the latest 2019 concepts in applying Deep Learning to Computer Vision, look no further – this is the course for you! You’ll get hands  the following Deep Learning frameworks in Python:

  • Keras
  • Tensorflow
  • TensorFlow Object Detection API
  • YOLO (DarkNet and DarkFlow)
  • OpenCV
  • All in an easy to use virtual machine, with all libraries pre-installed!

    ======================================================

    Apr 2019 Updates:

  • How to setup a Cloud GPU on PaperSpace and Train a CIFAR10 AlexNet CNN almost 100 times faster!
  • Build a Computer Vision API and Web App and host it on AWS using an EC2 Instance!
  • Mar 2019 Updates:

    Newly added Facial Recognition & Credit Card Number Reader Projects

  • Recognize multiple persons using your webcam
  • Facial Recognition on the Friends TV Show Characters
  • Take a picture of a Credit Card, extract and identify the numbers on that card!
  • ======================================================

    TinyURL for this post: https://tinyurl.com/yymjvksb

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