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Project #2: Tableau Story Visualization of Russian Federation Losses During the Full-Scale Russo-Ukrainian War

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Table of Contents Project Summary Disclaimer Learning Outcomes Data Sources Story Discussion by Worksheet                   Bar Graph - Visually Confirmed Losses of Russian Federation Equipment           Pie Graph - Selected Visually Confirmed Losses of Russian Federation Ground Equipment by Type           Tree Map - Selected Visually Confirmed Losses of Russian Federation Ground Equipment by Model           Line Graph - Daily KIA of Russian Federation In the First Year of Full-Scale War Conclusion Project Summary Given the one-year anniversary of the full-scale war between Russia and Ukraine, I decided to visualize the losses of the Russian Army sustained over the course of the past year using Tableau Public. A rather morbid topic, but an important one that should be talked about. As of the writing of this post, 150,000 is the official Wester...
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Project #1: Neural Networks for Concrete Compressive Strength Predictions - An Exercise in Deep Learning Modeling

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https://github.com/artemkk/flask-api/tree/master Table of Contents Project Summary Learning Outcomes Project Premise Starting Goals Constraints & Unknowns Project Topics API Process Results Similarities & Differences Learning Outcomes & Improvements Data Set & Data Exploration Process Results Similarities & Differences Learning Outcomes & Improvements Database Process Results Similarities & Differences Learning Outcomes & Improvements Neural Network Model Process Results Similarities & Differences Comparison Learning Outcomes & Improvements Yeh's Validation Experiment & Use Case Conclusion Citation Project Summary I made a Flask API that pulls data from a local PostgreSQL database and pushes it into a *feed-forward* neural network in the aim of predicting concrete compressive strength based on eight constituent features. After doing so, I read the academic paper [1] that sourced me with this data set for the first time. This was don...
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