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Moaaz900

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using Python, data source (Data.Gov) Studied MDN published materials and summarized its theory and applications Applied MDN on Airlines-On-Time Performance Data to predict arrival delay distribution and its uncertainty conditioned on departure delay

Clustering-COVID-19-Research-Papers-

using Databricks platform, data source (Kaggle) Clustered technical papers, using K-means algorithm, to easily find the related papers Recommended top (N) similar papers, from the relevant cluster using cosine similarity

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Moaaz900

Config files for my GitHub profile.

BBC-news-articles

Developed classification model using transfer learning Bert and Xl-net to predict BBC articles classes like sport, economic, entertainment,...etc.

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Customer-Churn-Management-

Segmented customers using K-means algorithm Predicted customers churn using Logistic Regression Applied Naïve Bayes classifier with Cross Validation to enhance customer churn prediction

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New-York-City-Taxi-Rides-Analytics

Calculated the average time it takes for taxi to find it next trip per destination borough Computed the number of trips that started and ended within same borough Determined the number of trips that start in one borough and ended in another one

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ETL-based-on-TPC-DI

Populated dimensions according to its schema from different data sources (xml, txt, csv) files Created FactCashBalances table from these dimensions Performed queries on FactCashBalances

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Cardiovascular-Disease-Risk-Detection

Estimated Naïve Bayes-based risk; using vital signs, gender, serum cholesterol and other features; of a person developing a heart disease

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Passenger-Flights-Planning-Model-Based-on-Airlines-On-Time-Performance-Data-

Predicted arrival flight delay time using both Decision Tree method with N-Fold Cross Validation and Random Forests method with Bagging Compared the prediction performance of the two methods

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Chicago-crime-rates

Data source (Chicago Data Portal), collected and joined data that describes all aspects of Chicago's community area income, poverty, unemployment, education, birth rate, health, etc. Applied Cross Validation on multiple regression algorithms to select the best model Developed regression model using XGBRegressor algorithm to predict rates of crime types at specific community areas and specific parts of the day with the random search technique to tune hyperparameters

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Loans-charged-off

Applied Cross Validation on multiple regression algorithms to select the best model Developed regression model using XGBRegressor algorithm to predict charged-off amount if defaulted with the random search technique to tune hyperparameters

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Moaaz900/Studying-and-applying-Mixture-Density-Network-MDN-

Moaaz900

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