Implementing Deep Learning Concepts Through Neural Networks

In this webinar, we will discuss the implementation of deep learning concepts through neural networks. After looking at the brief history, we will learn the basics about the inner workings of a typical neural network. We willl also look in into the proper scenarios in which neural networks should or should not be utilized. Finally, we will briefly look into the practical application of neural networks and deep learning.

You Will Learn How To:

  • Develop a basic understanding of implementing a series of algorithms to mimic the operations of a human brain to recognize relationships between vast amounts of data.
  • Embrace and extract valuable insights from textual data for continuous and learned improvement.
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Presented by Imran Ahmad

Imran has more than 15 years of technical expertise in designing software architectures, conducting data research, and other IT-related services. As part of his Ph.D. research, he developed a Linear Programming based algorithm called ATSRA that optimally processes information for Big Data. He has also designed and implemented a Hadoop cluster for data processing. In addition to developing state-of-the-art algorithms and techniques to develop these models, Imran is working with the Canadian Immigration Department to develop a predictive analytics model that can automate the Canadian immigration and Visa processes.