$125 | Duration: 2h4m | Video: h264, 1896x1056 | Audio: AAC, 48kHz, 2 Ch | 415 MB
Genre: eLearning | Language: English | January 31, 2019

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

Video Description
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.

The code bundle for this video course is available at - https://github.com/PacktPublishing/Hands-On-Deep-Learning-for-Computer-Vision

Style and Approach
This video course offers a project-based approach to teach you the skills required to develop computer vision applications using Deep Learning and Python.

Table of Contents
DL OVERVIEW AND DENOISING IMAGES WITH AUTOENCODERS
IMAGE CLASSIFICATION WITH KERAS
CONSTRUCT A GAN WITH KERAS
OBJECT DETECTION WITH YOLO
GENERATING IMAGES WITH NEURAL STYLE

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

Authors
Jakub Konczyk
Jakub Konczyk has enjoyed programming professionally since 1995. He is a Python and Django expert and has been involved in building complex systems since 2006. He loves to simplify and teach programming subjects and share his knowledge with others. He first discovered Machine Learning when he was trying to predict real estate prices in one of the early stage startups he was involved in. He failed miserably. Then he discovered a much more practical way to learn Machine Learning that he would like to share with you in this course. It boils down to the Keep it simple! mantra.
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