Author: Deep Learner

Deep Learning

DeLighT: Very Deep and Light-weight Transformers

DeLighT: Very Deep and Light-weight Transformers This repository contains the source code of our work on building efficient sequence models: DeFINE (ICLR’20) and DeLighT (preprint). Overview In this repository, we share the source code of our paper DeLight, that delivers similar or better performance thantransformer-based models with significantly fewer parameters. DeLighT more efficiently allocates parameters both (1)within each Transformer block using DExTra, a deep and light-weight transformation and (2) across blocks usingblock-wise scaling, that allows for shallower and narrower DeLighT […]

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Machine Learning

A powerful and flexible machine learning platform for drug discovery

TorchDrug TorchDrug is a PyTorch-based machine learning toolbox designed for several purposes. Easy implementation of graph operations in a PyTorchic style with GPU support Being friendly to practioners with minimal knowledge about drug discovery Rapid prototyping of machine learning research Installation TorchDrug is compatible with Python >= 3.5 and PyTorch >= 1.4.0. From Conda conda install -c milagraph -c conda-forge torchdrug From Source TorchDrug depends on rdkit, which is only available via conda.You can install rdkit with the following line. […]

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Wrapper

A lightweight wrapper for the IG Markets API written in Python

trading_ig A lightweight wrapper for the IG Markets API written in Python. Simplifies access to the IG REST and Streaming APIs with a live or demo account. What is it? IG Markets provides financial spread betting and CFD platforms for trading equities, forex, commodities, indices, cryptocurrencies, bonds, rates, options and more. IG provide APIs so that developers can access their platforms programmatically. Using the APIs you can get live and historical data, automate your trades, or create apps. For details […]

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Research

Python implementation of the multistate Bennett acceptance ratio

pymbar Python implementation of the multistate Bennett acceptance ratio (MBAR) method for estimating expectations and free energy differences from equilibrium samples from multiple probability densities. Installation The easiest way to install the pymbar release is via conda: conda install -c conda-forge pymbar You can also install pymbar from the Python package index using pip: pip install pymbar The development version can be installed directly from github via pip: pip install git+https://github.com/choderalab/pymbar.git Usage Basic usage involves importing pymbar and constructing an […]

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Transformer

Transform-Invariant Non-Negative Matrix Factorization

Transform-Invariant Non-Negative Matrix Factorization A comprehensive Python package for Non-Negative Matrix Factorization (NMF) with a focus on learning transform-invariant representations. The packages supports multiple optimization backends and can be easily extended to handle application-specific types of transforms. A general introduction to Non-Negative Matrix Factorization and the purpose of this package can be found on the corresponding GitHub Pages. For using this package, you will need Python version 3.7 (or higher).The package is available via PyPI. Installation is easiest using pip: […]

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Tool

Library to interact with the lbrynet client from the LBRY project

A library of functions that can be used to manage the download of claims from the LBRY network. It includes methods to download claims by URI (canonical url), claim ID, or from specific channels. It also includes methods to clean up older files and free space, so the functions are suitable for use in a headless computer that will download files, and seed them to the network with little user intervention. This libary is released as free software under the […]

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Monitoring

Performance monitoring and testing of OpenStack

Browbeat Browbeat is a performance tuning and analysis tool for OpenStack. Browbeat is free, Open Source software. Analyze and tune your Cloud for optimal performance. Create Rally workloads for performance and scale testing. Automate deployment of common data analysis tools. Documentation Browbeat documentation is available at https://browbeat.readthedocs.io/ GitHub https://github.com/cloud-bulldozer/browbeat    

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Documentation

A document format conversion service based on Pandoc

reformed Document format conversion service based on Pandoc. Usage The API specification for the Reformed server is as follows: GET /api/v1/formats: Lists available input and output formats for documents Response { “input”: { “commonmark”: { “mime”: “text/markdown”, “ext”: “md”, “detail”: “CommonMark Markdown” }, “docx”: { “mime”: “application/vnd.openxmlformats-officedocument.wordprocessingml.document”, “ext”: “docx”, “detail”: “Word docx” }, // … }, “output”: { “commonmark”: { “mime”: “text/markdown”, “ext”: “md”, “detail”: “CommonMark Markdown” }, “docx”: { “mime”: “application/vnd.openxmlformats-officedocument.wordprocessingml.document”, “ext”: “docx”, “detail”: “Word docx” }, // … […]

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Flask

Library books management web application built with Flask

library books management Web application Library books management web application built with Flask Upload a book to the database, and also see it at home page. You’ll be able to edit the book if you make a mistake while registering it. Borrow a book to the customer and register the borrowed date. You’ll be able to see the borrowed books information. You’ll be able to edit the borrowed books information. You’ll be able to see the returned books information If […]

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Advanced, NLP, Project, Python, Text, Unstructured Data

New Anaphora and Co-reference Resolution Technique for Biographies

This article was published as a part of the Data Science Blogathon Introduction Biographies of many famous personalities are very insightful and inspiring. Although, one may not want to read the whole document. In order to just get the important points from the biography, one can generate a summary of the biography. The summary is generated by giving weights to all the words. Sometimes, anaphoras can be predicted by the machine as a separate word which in return produces a less […]

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