Tutorial Questions | Week 4 COSC2779 – Deep Learning This tutorial is aimed at reviewing optimization techniques and regularization in deep learning. Please try the questions before you join the session. 1. Calculate the gradient update for the neural network below with given initialized weights, if the input data point is x = [1, 2] […]
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Tutorial Questions | Week 2 COSC2779 – Deep Learning This tutorial is aimed at reviewing basic machine learning concepts. Please try the questions before you join the session. 1. A computer program is said to learn from experience E with respect to some task T and some performance measure P if its performance on T,
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COSC2779LabExercises_W09_BERT ¶ COSC 2779 | Deep Learning ¶ Week 9 Lab Exercises: **Classify text – BERT** ¶ Introduction¶ In this tutorial, you will learn how to classify text by using transfer learning from a BERT model. A pre-trained model is a saved network that was previously trained on a large dataset, typically on a large-scale
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COSC2779LabExercises_W7 Lab Exercises – Week: 7¶ COSC2779 – Deep Learning – 2020 This lab is aimed at understanding how to develop a simple RNN for sentiment classification. During this lab you will: Encode/Decode text data Develop a many-to-one RNN model for sentiment classification This notebook is designed to run on Google Colab. If you like
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Tutorial Questions | Week 6 COSC2779 – Deep Learning This tutorial is aimed at reviewing famous CNN architectures. Please try the questions before you join the session. 1. The GoogLeNet uses inception modules as the basic building block. (a) Why does inception module have multiple paths? Solution: choosing the right kernel size for the convolution
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Tutorial Questions | Week 7 COSC2779 – Deep Learning This tutorial is aimed at reviewing practical methodology in developing CNN. Please try the questions before you join the session. The question below has similar structure to the case study questions that you can expect in the end semester test. 1. You have been hired by
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Deep Learning – COSC2779 – Introduction to Deep Learning Deep Learning – COSC2779 Introduction to Deep Learning Dr. Ruwan Tennakoon Semester 2, 2021 Reference: Chapter 5: Ian Goodfellow et. al., “Deep Learning”, MIT Press, 2016. Lecture 1 (Part 2) Deep Learning – COSC2779 Semester 2, 2021 1 / 40 Outline 1 What is Deep Learning?
Deep Learning – COSC2779 – Deep Learning Hardware and software Deep Learning – COSC2779 Deep Learning Hardware and software Dr. Ruwan Tennakoon July 26, 2021 Lecture 2 (Part 2) Deep Learning – COSC2779 July 26, 2021 1 / 19 Why Now? Big Data Larger Data sets. Easier collection and storage. Computation Graphic Processing Units. Massively
COSC2779LabExercises_W5_solutions ¶ COSC 2779 | Deep Learning ¶ Week 5 Lab Exercises: **Data loader and Augmentation** ¶ Introduction¶ This lab is aimed at understanding how to write your own data loader and learn the importance of data augmentation. During this lab you will: Learn to do data augmentation Explore different data loading mechanisms in TensorFlow
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Deep Learning – COSC2779 – Sequential Data – Applications Deep Learning – COSC2779 Sequential Data – Applications Dr. Ruwan Tennakoon Sep 13, 2021 Reference: Chapter 10: Ian Goodfellow et. al., “Deep Learning”, MIT Press, 2016. Lecture 8 (Part 1) Deep Learning – COSC2779 Sep 13, 2021 1 / 43 Outline 1 Text Classification Word Embedding