This workshop is an introduction to how deep learning works and how you could create a neural network using TensorFlow v2. We start by learning the basics of deep learning including what a neural network is, how information passes through the network, and how the network learns from data through the automated process of gradient descent. You would build, train and evaluate your very own network using a cloud GPU (Google Colab).
We then proceed to look at image data and how we could train a convolution neural network to classify images. You will extend your knowledge from the first part to design, train and evaluate this convolutional neural network.
This workshop is targeted at professionals with some data science knowledge who would like a theoretical and hands-on introduction to deep learning. The workshop assumes background knowledge in Python programming, understanding of basic data science concepts such as training vs. testing data, overfitting, and regression. A high level understanding of calculus and matrix operations is beneficial but not essential.