TensorFlow has been
gaining immense popularity over the past few months, due to its power
and simplicity to use. This video will help you leverage the power of
TensorFlow to perform advanced image processing. This course is a
continuation of the Intro to Computer Vision course, building on top of
the skills learned in that course. In this course, you’ll dive deeper as
we cover more advanced computer vision concepts.
You will implement
multiple state-of-the-art deep learning papers from scratch using the
TensorFlow-Keras API. This course will teach you how to construct
efficient CNN architectures with CNN Squeeze layers and delayed
downsampling . You’ll learn about residual learning with skip
connections and deep residual blocks, and see how to implement a deep
residual neural network for image recognition. You’ll find out about
Google’s Inception module and depthwise separable convolutions and
understand how to construct an extreme Inception architecture with
TF-Keras.
Finally, you’ll be
introduced to the exciting new world of adversarial neural networks,
which are responsible for recent breakthroughs in synthetic image
generation and implement an auxiliary conditional GAN.
Author
Marvin Bertin has
authored online Deep Learning courses. Marvin is the technical editor of
a deep learning book and a conference speaker. He has a bachelor’s
degree in Mechanical Engineering and Masters in Data Science.
Marvin has worked at a
deep learning start-up developing neural network architectures. He is
currently working in the biotech industry building NLP machine learning
solutions. At the forefront of next generation DNA sequencing, he builds
intelligent applications with Machine Learning and Deep Learning for
precision medicine.
