{"id":10,"title":"Introduction to Deep Learning and TensorFlow","url":"https://doi.org/10.26180/13100519","description":"This workshop is intended to run as an instructor guided live event and consists of two parts. Each part consists of a lecture and a hands-on coding exercise.\r\nPart 1 - Introduction to Deep Learning and TensorFlow\r\nPart 2 - Introduction to Convolutional Neural Networks\r\nThe Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises.\r\n\r\nThis 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. Workshop attendees would build, train and evaluate a neural network using a cloud GPU (Google Colab).\r\nIn part 2, we look at image data and how we could train a convolution neural network to classify images. Workshop attendees will extend their knowledge from the first part to design, train and evaluate this convolutional neural network.","doi":"","licence":"CC-BY-4.0","contact":"datascienceplatform@monash.edu ","keywords":["deep learning","tensorflow","convolutional neural network","machine learning"],"remote_updated_date":null,"remote_created_date":null,"created_at":"2021-08-31T05:21:38.589Z","updated_at":"2021-09-07T10:35:07.988Z","content_provider_id":15,"target_audience":[],"authors":["Titus Tang"],"contributors":[],"subsets":[],"resource_type":[],"other_types":"","version":"","status":"active","date_created":null,"date_modified":null,"date_published":null,"prerequisites":"","syllabus":"","learning_objectives":"","fields":[],"scientific_topics":[],"operations":[]}