Discover @Moaaz900 Open Source projects

Moaaz Youssef (@Moaaz900)

Moaaz900

Stars
15
Global Rank 765,281 (Top 27 %)
Followers 1
Following 1
Registered about 5 years ago
Most used languages

Jupyter Notebook
100.0 %
Location 🇪🇬 Egypt
Country Total Rank 1,733
Country Ranking

Jupyter Notebook
132

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

Jupyter Notebook

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.

Jupyter Notebook

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

Jupyter Notebook

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

Jupyter Notebook

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

Jupyter Notebook

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

Jupyter Notebook

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

Jupyter Notebook

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

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

Jupyter Notebook

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

Jupyter Notebook

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

Jupyter Notebook