Hands-On Deep Learning for Computer Vision

Go from auto encoding to cutting-edge imaging techniques such as YOLO and Neural Doodle with Keras, TensorFlow, OpenCV, and Python

Machine Learning, and Deep learning techniques in particular, are changing the way computers see and interact with the World. From augmented and mixed-reality applications to just gathering data, these new techniques are revolutionizing a lot of industries This course is designed to give you a hands-on learning experience by going from the basic concepts to the most current in-depth Deep Learning methods for Computer Vision in use today.

In this course, you will be introduced to the concept of deep learning and a variety of popular and effective techniques for image classification, detection, segmentation and generation. You will learn to build your own neural network and classify images accordingly. You will be taken through popular techniques such as Deep Dream (to generate psychedelic, surreal images), Style Transfer (to transfer styles between images), and Neural Doodle, to generate an image that matches a doodled sketch.

By the end of this course, you will be able to use computer vision and deep learning to encode, classify, detect, and style images for the real world.

What You Will Learn

Hands-on experience using deep learning with Python, Keras, TF, and OpenCV
Encode, decode, and denoise images with autoencoders
Understand the structure and function of neural networks and CNNs/pooling
Classify images with OpenCV using smart Deep Learning methods
Detect objects in images with You Only Look Once (YOLOv3)
Work with advanced imaging tools such as Deep Dream, Style Transfer, and Neural Doodle