Subject ▸ deep learning

A Deep Learning virtual machine with PyTorch and TensorFlow

Introduction This is a VirtualBox VM that is automatically generated using Vagrant. Machine Learning and Deep Learning packages installed are: Scikit-Learn, NLTK, Keras, TensorFlow and PyTorch. A Vagrant file is used to generate this VM based on Ubuntu 16.04 (xenial64). Getting Started This VM should work in Windows, macOS and Linux (tested in Debian-10 Buster) VirtualBox (version 6+) is required Download and install Vagrant

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Using application microprocessors for seismic

First practical application that I know of using the next thing after TPUs (Tensor Processing Units): ASICs or Application Specific Integrated Circuit. Ideal dedicated hardware for the massive seismic data and processing. Machine Learning (ML) algorithms build a mathematical model based upon representative sample data, known as ‘training data’, in order to make predictions or decisions without being explicitly programmed to perform the task. I limit my discussion here to supervised learning in the context of a potential application to seismic data image processing of a real marine seismic dataset, and then discuss how the computational scale of such exercises reinforce the need to develop computing technology that is customized for large ML problems.

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