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Long story short: “A family of parametric, non-linear and hierarchical representation learning functions, which are massively optimized with stochastic gradient descent to encode domain...
What is Deep Learning? Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. Deep Learning by Y. LeCun et al. Nature 2015. Artificial Intelligence.
25 cze 2018 · This is a deep learning presentation based on Deep Neural Network. It reviews the deep learning concept, related works and specific application areas.It describes a use case scenario of deep learning and highlights the current trends and research issues of deep learning. Read more. 1 of 79.
This repo contains lecture slides for Deeplearning book. This project is maintained by InfoLab @ DGIST (Large-scale Deep Learning Team), and have been made for InfoSeminar. It is freely available only if the source is marked.
7 sie 2017 · Deep Learning Explained. This document summarizes Melanie Swan's presentation on deep learning. It began with defining key deep learning concepts and techniques, including neural networks, supervised vs. unsupervised learning, and convolutional neural networks.
Overview. Motivation for deep learning. Areas of Deep Learning . Convolutional neural networks . Recurrent neural networks. Deep learning tools.
Option 1: Proposal. Groups. Present research. 3 minutes. List of example website: Presentations. Submit groups 5pm to. Submit slide to be eligible. Option 2: Write a 1-page review.
