Deep Learning – COSC2779 – Neural Network Optimization Deep Learning – COSC2779 Neural Network Optimization Dr. Ruwan Tennakoon August 2, 2021 Reference: Chapter 7,8: Ian Goodfellow et. al., “Deep Learning”, MIT Press, 2016. Lecture 3 (Part 1) Deep Learning – COSC2779 August 2, 2021 1 / 56 Outline Part 1: Optimization Techniques 1 Loss Function […]
Deep Learning – COSC2779 – Representation Learning Problems in Applying Deep Learning When applying deep learning in practice: Usually, deep network architectures are required for complex tasks. They have many parameters and need large labeled datasets to obtain good generalization. Generating large ”labeled” dataset for your task is di�cult. Time consuming: You may want to
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Deep Learning – COSC2779 – Practical methodology & Hyperparameter tuning Deep Learning – COSC2779 Practical methodology & Hyperparameter tuning Dr. Ruwan Tennakoon Aug 23, 2021 Reference: Chapter 11: Ian Goodfellow et. al., “Deep Learning”, MIT Press, 2016. Lecture 6 (Part 1) Deep Learning – COSC2779 Aug 23, 2021 1 / 28 Outline 1 Practical Methodology
Deep Learning – COSC2779 – Modelling Sequential (Time Series) Data Deep Learning – COSC2779 Modelling Sequential (Time Series) Data Dr. Ruwan Tennakoon Sep 6, 2021 Reference: Chapter 10: Ian Goodfellow et. al., “Deep Learning”, MIT Press, 2016. Lecture 7 (Part 1) Deep Learning – COSC2779 Sep 6, 2021 1 / 39 MAIA – AI for
Deep Learning – COSC2779 – Convolutional Neural Networks Deep Learning – COSC2779 Convolutional Neural Networks Dr. Ruwan Tennakoon August 9, 2021 Reference: Chapter 9: Ian Goodfellow et. al., “Deep Learning”, MIT Press, 2016. Lecture 4 (Part 1) Deep Learning – COSC2779 August 9, 2021 1 / 42 Outline 1 Motivation 2 2D Convolution in Traditional
Deep Learning – COSC2779 – Deep Feed Forward Networks Deep Learning – COSC2779 Deep Feed Forward Networks Dr. Ruwan Tennakoon July 26, 2021 Reference: Chapter 6: Ian Goodfellow et. al., “Deep Learning”, MIT Press, 2016. Lecture 2 (Part 1) Deep Learning – COSC2779 July 26, 2021 1 / 46 Outline Part 1: Deep Feed Forward
Tutorial Questions | Week 3 COSC2779 – Deep Learning This tutorial is aimed at reviewing feed forward neural networks. Please try the questions before you join the session. 1. For a fully-connected deep network with one hidden layer, increasing the number of hidden units should have what effect on bias and variance? 2. Consider the
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Deep Learning – COSC2779 – Vision Application & CNN Architectures Deep Learning – COSC2779 Vision Application & CNN Architectures Dr. Ruwan Tennakoon Aug 16, 2021 Lecture 5 (Part 1) Deep Learning – COSC2779 Aug 16, 2021 1 / 51 Outline 1 Image Classification AlexNet VGGNet GoogLeNet ResNet 2 Object Detection & Segmentation Lecture 5 (Part
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_W2_3_solutions ¶ COSC 2779 | Deep Learning ¶ Week 1-2 Lab Exercises: **Introduction to Tensorflow** ¶ introduction¶ This lab is aimed at introducing the fundamentals of TensorFlow 2.0. The Lab is organized into six sub modules: Minimal example: 2D Linear regression. Exercise: Classifying hand written text MNIST. Advanced TensorFlow example: Understanding gradient tape and writing