Overview

Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills for free at our R workshops!

This workshop provides a brief history of Artificial Neural Networks (ANN) and an explanation of the intuition and concepts behind them with few mathematical barriers. Participants will learn step-by-step construction of a basic ANN. Also, you will use the popular scikit-learn Python library to implement an ANN on a classification problem. High-level libraries reduce the work for a researcher implementing ANN down to tuning a set of parameters, which will also be explained in this part.

This training will help you navigate the copyright, fair use, and usage rights of including third-party content in your digital project. Whether you seek to embed video from other sources for analysis, post material you scanned from a visit to the archives, add images, upload documents, or more, understanding the basics of copyright and discovering a workflow for answering copyright-related digital scholarship questions will make you more confident in your publication. We will also provide an overview of your intellectual property rights as a creator and ways to license your own work.

This workshop introduces the basic concepts of Deep Learning - the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data. Like many other machine learning algorithms, we will use deep learning algorithms to map input data to their appropriately classified outcome labels.