Fundamentals of Deep Learning for Multiple Data Types

Programme Overview

This workshop uses a series of hands-on exercises to teach deep learning techniques for a range of problems involving multiple data types. After a quick introduction to deep learning, you’ll advance to building deep learning applications for image segmentation, sentence generation, and image and video captioning, while learning relevant computer vision, neural network, and natural language processing concepts. At the end of the workshop, you’ll be able to assess a broad spectrum of problems where deep learning can be applied.

Course Content

At the conclusion of the workshop, you’ll have an understanding of the fundamentals of deep learning for multiple data types and be able to:

  • Implement common deep learning workflows such as image segmentation and text generation
  • Compare and contrast data types, workflows, and frameworks
  • Combine deep learning-powered computer vision and natural language processing to start solving sophisticated real-world problems that require multiple input data types

Key Information


Familiarity with basic Python (functions and variables); prior experience training neural networks

Libraries, Tools & Framework

TensorFlow, TensorBoard

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