Tensorflow from Zero to Hero

Join us to learn about the basics of building neural networks for software engineers, through neural weights and biases, activation functions, supervised learning, and gradient descent. We will start with low-level Tensorflow and include a sample of high-level Tensorflow code using layers and data sets.

Nov 19, 2022, 3:00 – 4:00 PM

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Key Themes

Career DevelopmentMachine Learning

About this event

This talk will cover the basics of building neural networks for software engineers, through neural weights and biases, activation functions, supervised learning, and gradient descent. I'll show you some tips and best practices for effective training, such as learning rate decay, gradient descent regularization, and the subtleties of overfitting. Be aware that dense and convolutional neural networks are key to any modern implementation. This session starts with low-level Tensorflow and also includes a sample of high-level Tensorflow code using layers and data sets.

Speaker

  • Nadia Tahiri

    University of Sherbrooke

    Assistant Professor

Facilitator

  • Jolina Li

    GDSC Lead

Organizers

  • Aurora Zhang

    GDSC Lead

  • Aniedi Udo-Obong

    Regional Leader

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