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Introduction to TensorFlow Workshop

  • Dalhousie University Goldberg Computer Science Building (Room 426, ShiftKey Labs) 6050 University Ave. Halifax, NS Canada (map)

Are you short on time to start from scratch to use deep learning to solve complex problems involving topics like neural networks and reinforcement learning? If yes, then this is the workshop to help you.

This workshop is designed to help you to overcome various data science problems by using efficient deep learning models built in TensorFlow.

The workshop begins with an introduction to TensorFlow essentials. Next, we start with deep neural networks for different problems and then explore the applications of Convolutional Neural Networks on a real dataset. If you’re facing time series problem then we will show you how to tackle it using RNN.

If the time permits then we can have other implementations of the models as well. All these will be developed with step-by-step TensorFlow implementation with the help of real examples.

By the end of the workshop you will be able to start developing deep learning-based solutions without any need to learn deep learning models from scratch, rather using TensorFlow and it’s enormous power.


A basic familiarity with Machine Learning is helpful, but not required.

All participants must complete the following in advance of the workshop:

Instructor Bio

Data Science Researcher at the Institute for Big Data Analytics, Dalhousie University

Salil Vishnu Kapur is a Data Science Researcher at the Institute for Big Data Analytics, Dalhousie University. He is extremely passionate about Machine Learning, Deep Learning, Data mining and Big Data Analytics. Currently working as a Researcher at Deep Vision and prior to that worked as a Senior Analyst at Capgemini for around 3 years with these technologies. Prior to that Salil was an intern at IIT Bombay through the FOSSEE Python TextBook Companion Project and presently with the Department of Fisheries and Transport Canada through Dalhousie University.

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