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Our core product is known as the Arria NLG Platform, a form of artificial intelligence software that specializes in extracting information from complex data sources and communicating that information in natural language. Arria is the leader in real-time data storytelling. This software implements several machine learning algorithms using the MapReduce framework.

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When you’re ready to get started, Chris or Ilana can show you where to go on our system. The distributed file system is called Hadoop. You can learn about MapReduce by reading this paper, or if you’re wanting something more in-depth, you can watch this lecture series.

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For those wishing to try out MapReduce code on a computing cluster, a la Google, Hadoop is set up on the Slate machines. For instance, Git and Mercurial offer some features that make collaboration easier, have better branching capabilites, and more intuitive command line incantations. There are a few new programs out there that improve on software like Subversion for doing distributed version control. While that may seem paradoxical, it is useful when dealing with files larger than git can currently easily handle, whether due to limitations in memory, time, or disk space. git-annex allows managing files with git, without checking the file contents into git. Python library for neural networks that supports GPU operations. There is also a probabilistic programming framework within PyTorch called Pyro (Sept 2021) PyTorch is the successor of Torch for Python. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. Torch is a scientific computing framework with wide support for machine learning algorithms.

There is also a probabilistic programming framework within TensorFlow called TensorFlow Probability (Sept 2021) The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. Tensorflow is an open source software library for numerical computation using data flow graphs.

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NVIDIA’s Academic Programs Team is dedicated to empowering and collaborating with professors and researchers at universities worldwide with: small scale GPU grants, graduate fellowships, free teaching materials, and NVIDIA developer access. Through lectures and programming assignments students will learn the necessary engineering tricks for making neural networks work on practical problems. On the model side we will cover word vector representations, window-based neural networks, recurrent neural networks, long-short-term-memory models, recursive neural networks, convolutional neural networks as well as some very novel models involving a memory component. The final project will involve training a complex recurrent neural network and applying it to a large scale NLP problem. Stanford’s Deep Learning for NLP course provides a deep excursion into cutting-edge research in deep learning applied to NLP.

Stanford Deep Learning for Natural Language Processing.

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The MS Computational Network Toolkit is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph. (OSU Only) LabArchives is a cloud-based Electronic Lab Notebook application which allows users to electronically create, store, share and manage data. It’s a Jupyter notebook environment that requires no setup to use and runs entirely in the cloud. Colaboratory is a Google research project created to help disseminate machine learning education and research. Each week at our computational linguistics discussion group, Clippers, we spend the first few minutes discussing interesting, time-saving, or just plain nifty tools that we’ve found.

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