The Complete Life Cycle of Data: From Exploration to Deployment
April 15th, 2021

The purpose of this article is to summarize the predictive modeling process, from exploring the data to deploying the prediction. This includes the thought process behind various decisions during the process, be it selecting the features that could help with better pred

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NLP Analysis and Feature Engineering: Untangling the Data To Help NGOs Get Funding
March 4th, 2021

A Natural Language Processing (NLP) analysis pipeline walkthrough for feature extraction, scraping Twitter, Google, and 1200 PDF files through automated APIs. The overall approach allowed us to gather data that visualizes several billion dollars of not for profit grant

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Visualizing Climate Change Impacts and Nature Based Solutions
December 27th, 2020

Applying various data science tools and methods to visualize climate change impacts. By Nishrin Kachwala, Debaditya Shome, and Oscar Chan Day by day, as we generate exponentially more data, we also sift through its complexity and consume more. Filtering out relevancy is

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AI for Disaster Response: Predicting Relief During Cyclones
December 4th, 2020

AI technology can be applied for disaster response and to predict the number and type of food and non-food items during a cyclone strike. The applications can be applied to other disaster types.   By Dev Bharti, Juber Rahman, Xavier Torres, and Rosana de Oliveira G

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Exploring Scientific Literature on Online Violence Against Children Using Natural Language Processing
November 23rd, 2020

The following work is part of the Omdena AI Challenge on preventing online violence against children, implemented in collaboration with John Zoltner at Save the Children US. This article is written by Wen Qing Lim, Maria Guerra-Arias, Sijuade Oguntayo   Tex

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