AI for Image Processing

Understand and implement state-of-the-art image-processing models (CNN, GAN, Auto-encoder) with TensorFlow 2 / Keras.

Get Course Info

Audience: Developers · Data Analysts · Data Scientists

Duration: 3 days

Format: Lectures & hands-on labs (50 % / 50 %)

Overview

AI algorithms for image analysis have made tremendous progress thanks to abundant data, affordable compute, and libraries such as TensorFlow. This course introduces Deep-Learning concepts plus TensorFlow and Keras, then dives into CNNs, GANs, Auto-encoders, and Transfer-Learning for computer-vision use-cases.

Objective

Understand and implement state-of-the-art image-processing models (CNN, GAN, Auto-encoder) with TensorFlow 2 / Keras.

What You Will Learn

Deep-Learning concepts
TensorFlow 2 and Keras APIs
Building neural networks & using TensorBoard
Deep Neural Networks
Convolutional Neural Networks (CNN)
Generative Adversarial Networks (GAN)
Auto-encoders
Transfer-Learning & benchmarking on CPU/GPU

Course Details