Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 44100 Hz
Language: English | VTT | Size: 8.79 GB | Duration: 14h 43m

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!
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
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
Update: June-2020
TensorFlow 2.0 Compatible Code
Windows install guide for TensorFlow2.0 (with Keras), OpenCV4 and Dlib
Deep Learning Computer Vision™ Use Python & Keras to implement CNNs, YOLO, TFOD, R-CNNs, SSDs & GANs + A Free Introduction to OpenCV.
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 2.0
TensorFlow Object Detection API
YOLO (DarkNet and DarkFlow)
OpenCV4
All in an easy to use virtual machine, with all libraries pre-installed!