December 2020
Introduction to Deep Neural Networks with Keras/TensorFlow
Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including the popular library TensorFlow. In this workshop, participants will learn…
Using Distill for R Markdown
There are a variety of formats available for R markdown beyond 'standard html', one of which is Distill. Distill is specifically oriented toward presentation of results, and offers a clean…
Spatial regression models
This lecture-style workshop will introduce relevant concepts and techniques for modelling cross-sectional data observed on regular (such as remote sensing pixels) or irregular (such as Census polygons) lattice. Such data…
January 2021
Introduction to Python’s NumPy library
This workshop will introduce you to the NumPy library in Python, which is useful in scientific computing. We will cover NumPy’s n-dimensional array object and associated functions in depth, along…
February 2021
Image Segmentation using Deep Learning with FastAI
Like many image processing problems, deep learning has brought many effective solutions to the task of image segmentation. This workshop will introduce you to the methods used in image segmentation,…
March 2021
Introduction to Deep Neural Networks with Keras/TensorFlow
Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network…
April 2021
Object Detection using Deep Learning with TorchVision
Like many image processing problems, deep learning has brought many effective solutions to the task of object detection. The TorchVision library is part of the PyTorch project, and it offers…