Predictig the salaries using numerical and categorical data from the dataset. Implemented using Python libraries such as pandas, numpy, seaborn, matplotlib, scikit-learn, mlextender, statsmodel.
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Finding the correlation between Total yearly compensation for an individual working in the STEM industry and the arrtibutes that affect this compensation the most. Discovered using Python libraries such as pandas, numpy, seaborn, and matplotlib.
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The International Development Association (IDA) credits are public and publicly guaranteed debt extended by the World Bank Group. IDA provides development credits, grants and guarantees to its recipient member countries to help meet their development needs. This project explores the public IDA dataset using various basic and advanced SQL queries.
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Visualizing some of the quries from 'IDA Statement Of Credits and Grants data exploration in SQL' using Tableau to provide a more intriguing way to grasp the data
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Clustering different coffee bean variants together, we can use this information for targeted marketing. If a customer buys a variant, other similar variants can be recommended to them.
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Data-driven business process change proposal to Dognition company management about how to increase the numbers of tests users complete on their website.
Tableau Dashboard Project Description Dataset Used
The project mainly focuses on how the data is handled in an educational institution. The data model was created using ERWIN data modeler
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