Deep Learning, NLP, NMT, AI, ML
DataGenerator A Python Script to generate a massive volume of data in sql or csv format 1. Dependencies To install required dependencies run pip install -r requirements.txt 2. Execution To execute the script: python generator.py or python3 generator.py GitHub https://github.com/icrescenti/DataGenerator
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Paper-Reviewer Matcher A python package for paper-reviewer matching algorithm based on topic modeling and linear programming. The algorithm is implemented based on this article). This package solves problem of assigning paper to reviewers with constrains by solving linear programming problem. We minimize global distance between papers and reviewers in topic space (e.g. topic modeling can be Principal component, Latent Semantic Analysis (LSA), etc.). Here is a diagram of problem setup and how we solve the problem. Mind-Match Command Line Mind-Match […]
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brokenkey Tiny command-line utility for mapping broken keys to other positions. Installation Clone this repository using git: git clonehttps://github.com/lymnyx/brokenkey Install using pip or pip3: pip3 install brokenkey/ Usage Start brokenkey by opening a terminal window and typing: brokenkey Now just copy and paste the character of the broken key in, enter the character you want to replace and then it should be running. Info: It is currently possible to use the pynput Key variables as character to replace (example: key […]
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Here is deepparse. Deepparse is a state-of-the-art library for parsing multinational street addresses using deep learning. Use deepparse to Use the pre-trained models to parse multinational addresses, retrain our pre-trained models on new data to parse multinational addresses, retrain our pre-trained models with your own prediction tags easily. Read the documentation at deepparse.org. Deepparse is compatible with the latest version of PyTorch and Python >= 3.7. Countries and Results We evaluate our models on two forms of address data clean […]
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MIA is shorthand for “Multiparametric Image Analysis”. It is intended to be a complete image processing environment mainly targeted at the analysis and visualization of large amounts of MRI data. MRI data analysis often requires a complex succession of data processing pipelines applied to a set of data acquired in an MRI exam or over several MRI exams. This analysis may need to be repeated a large number of times in studies involving a large number of acquisition sessions. Such […]
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gpip is a package installer utility for GitHub public and private repositories, is a way to replace the copy-paste problem for individuals or organizations that have code inside repositories but cannot make it public, with gpip you can handle a repository with more than one package and have versioning and other capabilities. Features Install packages from private or public repositories Allow to use versioning, branch and path location from repositories Easy and powerfull syntax to declare packages. Command Line interface […]
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dialogflow-fulfillment dialogflow-fulfillment is a package for Python that helps developers to create webhook services for Dialogflow. The package provides an API for creating and manipulating response messages,output contexts and follow-up events in conversations. A simple example from dialogflow_fulfillment import QuickReplies, WebhookClient # Define a custom handler function def handler(agent: WebhookClient) -> None: “”” This handler sends a text message along with a quick replies message back to Dialogflow, which uses the messages to build the final response to the user. […]
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pyHype pyHype is a Python framework for developing parallelized Computational Fluid Dynamics software to solve the hyperbolic 2D Euler equations on distributed, multi-block structured grids. It can be used as a solver to generate numerical predictions of 2D inviscid flow fields, or as a platform for developing new CFD techniques and methods. Contributions are welcome! pyHype is in early stages of development, I will be updating it regularly, along with its documentation. The core idea behind pyHype is flexibility and […]
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Each new version of Python adds new features to the language. For Python 3.8, the biggest change is the addition of assignment expressions. Specifically, the := operator gives you a new syntax for assigning variables in the middle of expressions. This operator is colloquially known as the walrus operator. This tutorial is an in-depth introduction to the walrus operator. You will learn some of the motivations for the syntax update and explore some examples where assignment expressions can be useful. […]
Read moreHave you run into issues acquiring the right type of data for your machine learning (ML) projects? You’re not alone. Many teams do. And data is one of the key sticking points in starting AI initiatives at companies. In fact, according to IBM’s CEO, Arvind Krishna, data-related challenges are the top reason IBM clients have halted or canceled AI projects. Often what happens in practice is that the relevant ML training data is either not collected, or collected but the […]
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