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

[LeeAndro]

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

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!

What you'll 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

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 Sntation 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!