Understanding Youth Sentiments Through Artificial Intelligence
July 13th, 2021

In this article, we implemented a Data Analysis pipeline to understand youth sentiments, analyzing aspirations, fears, and thoughts of the youth through scraping the web and youth-led media. Going through their sentiment analysis during the pandemic and around different

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Predicting the Important Factors of a Successful Startup using SHAP Value
July 12th, 2021

A step-by-step guide on creating the machine learning model to help startups’ investments strategies by using a SHAP (SHapley Additive exPlanations) value to understand the contribution of each feature into the model, and the importance of each factor to a success

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Estimating Electricity Demand of Sub-Saharan Africa Using AI
July 8th, 2021

Sub-Saharan Africa has 600 million people who do not have access to electricity. In this study, we have been able to go beyond typical kWh/m² benchmarks and provide two linear models that can estimate residential electricity demand given a household’s monthly income

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Using Causal Inference: How Can AI Help People Slow Their Aging Down
June 16th, 2021

In this article, Omdena’s team uses Causal Inference, a powerful modeling tool for explanatory analysis, on multivariate observational datasets and Machine Learning, to predict the exact “path” of actions or set of daily actions introduced into oneR

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The 7 Most Important Features of a Successful Machine Learning Project
June 10th, 2021

Invaluable lessons from contributing to and leading tasks on an Omdena Machine Learning challenge with 50 collaborators. In this article, we share with you the 7 most important features of a successful machine learning project with a large team and on production level.

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