sapphire9-7 Goto Github PK

classify-anime

This is a random forest classifier that classifies whether the anime is good or not based on 6 features. The model has been saved and passed to a Flask model then deployed as a web page using HTML

cs50-assessments

This repository is dedicated to all my work so far, and so forth in the CS50 intro to DS course.

data-science-training-project-1

This project is completed as part of the Data Science training at Orange Jordan. This is the first part of the project where we were given the data, analyzed it, cleaned it, applied operations at it, and made it ML model ready.

decision-tree-heart-disease-classification

A decision tree model that classifies whether one is prone to have heart disease in the next ten years or not based on different features.

diabetes-detec-bagging

A ensemble machine learning model (Bagging) to predict diabetes based on different features.

eda-fast-food

Comprehensive EDA on the Fast Food dataset

extracting-emails-using-python-sql

This is a Python model that takes in a text file as an input and uses SQLITE3 to locate the emails in the file and extract the domain names and how many times emails have been received from each domain.

heart-disease-pred

This logistic regression model is built to predict the possibility of having heart disease within the next 10 years based on different features.

linear-reg-study

Studying the effect of fitting a linear regression model on insufficient data.

machine-learning-with-python-association-rules-3209139

This is a LinkedIn Learning repo for Machine Learning with Python: Association Rules.

machine-learning-with-python-logistic-regression-3211129

This is a LinkedIn Learning repo for Machine Learning with Python: Logistic Regeression.

ml-classification-with-ease

This repository simplifies ML classification with organized, efficient classification models. Ideal for all skill levels, it offers default models, hyperparameter tuning, feature selection, tree-specific operations, and more.

modules-and-operations-on-txt-file

This Python program first reads the txt file as a dictionary, the keys are the student names, and the values are a list of the students' marks. Operations such as finding the highest average, the highest mark, IQR, standard deviation.. etc are performed on the formed dictionary. This is a practice of modules, statistics, and dictionary operations.

processing-python-web-scraped-data

This project is split between creating a python web-scraper to scrape the web for info on ML related websites, processing the web-scraped data, and finally tokenizing it to use on ML models.

prodigy_ml_01

Task 1 of the Prodigy InfoTech ML internship which involves building a basic Linear Regression model. The used dataset is a "Houseprice" dataset.

prodigy_ml_02

Task 2 of the Prodigy InfoTech ML internship which involves clustering wine using the Kmeans clustering algorithm.

prodigy_ml_04

Task 4 of the Prodigy InfoTech ML internship which involves building a hand gesture recognition model using CNN.

python-specialization-assessments

This repository is dedicated to all my work so far, and so forth in the Python specialization offered by the University of Michigan.

qi-guide

wisonsin-bcdetec

Studying the Breast Cancer Wisconsin (Diagnostic) Dataset, training different classifiers (SVM, Naive Bayes, and Adaboost) and evaluating them on training, testing, and validation