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Nasri Binsaleh's Projects

cuisine-predictor icon cuisine-predictor

A Cuisine Predictor Python program using SVM classification model to predict the type of cuisine when given a list of ingredients.

dbms-project icon dbms-project

In this project, a database for a 'company' was designed and a web database application was developed to run several SQL queries.

faa-airman-qualification-prediction icon faa-airman-qualification-prediction

Employed cutting-edge Machine Learning and Deep Learning algorithms, including SVM, Random Forest, and Neural Networks, to develop a dynamic framework for assessing pilots' qualification using Python and prominent ML libraries such as scikit-learn, TensorFlow, and PyTorch.

heart-disease-classification icon heart-disease-classification

Implemented classification models on heart failure dataset to assess the likelihood of an event that can be attributed to cardiovascular disease with R

neural-data-science icon neural-data-science

This is a neural data science project to investigate relationships between music and depression using Neural Data Science Techniques

pd-text-extraction icon pd-text-extraction

This is a python project to extract daily incidents from police department's website and store the extracted text data in sql database.

r-t-test icon r-t-test

R application to compute t-test between populations

stroke-data-mining icon stroke-data-mining

An application to predict the risk of stroke by analyzing medical checkup data and personal metrics. Implemented weighted Naive Bayes, ID3 Decision Tree, and Random Forest models in Python.

text-redactor icon text-redactor

A Python program using Natural Language Processing (NLP) to redact sensitive information from texts. The redactor model was trained to redact sensitive information including names, email addresses, particular concepts, addresses, gender, phone numbers, and dates.

text-unredactor icon text-unredactor

This is the unredactor where the program can predict the what would be the most likely names that were in the texts before they were redacted.

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