Taught an introductory workshop introducing tensorflow, deep learning and image recognition with convolutional neural networks as part of the ABACBS (Australian Bioinformatics and Computational Biology Society) 2020 workshop series.
This workshop was an introduction to how deep learning works and how participants could create a neural network using TensorFlow v2. We started 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. Participants built, trained and evaluated their own networks using a cloud GPU (Google Colab).
We then proceeded to look at image data and how we could train a convolution neural network to classify images. Participants extended their knowledge from the first part to design, train and evaluate this convolutional neural network.
This workshop was 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 was beneficial but not essential.
This workshop was organised by ABACBS.