Deep Learning Computer Vision™ CNN, OpenCV, YOLO, SSD & GANs [Udemy Course]

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size11.1 GB
  • Uploaded Bymfp19
  • Downloads197
  • Last checkedMay. 10th '20
  • Date uploadedMay. 08th '20
  • Seeders 20
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Infohash : A1E6D4B17147253141A5F027001D54B5B2D8C927

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

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.

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




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