This repo has been developed for the Istanbul Data Science Bootcamp, organized in cooperation with IBB and Kodluyoruz. Prediction for house prices was developed using the Kaggle House Prices - Advanced Regression Techniques competition dataset.

• Updated Jul 10, 2022
• Jupyter Notebook

Forecasting Netflix Customer Retention based on Gaussian Process Regression

• Updated Jul 22, 2023
• Python

I have built a Model using the Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.

• Updated Feb 7, 2021
• Jupyter Notebook

Analyze and Build a machine learning (ML) model on the Iris Flower dataset

• Updated Jun 30, 2023
• Jupyter Notebook

Use Random Forest to prepare a model on fraud data. Treating those who have taxable income <= 30000 as "Risky" and others are "Good" and A cloth manufacturing company is interested to know about the segment or attributes causes high sale.

• Updated Feb 5, 2023
• Jupyter Notebook

A repo packed with common and important machine learning techniques and algorithm implementations using sklearn.

• Updated Apr 15, 2022
• Jupyter Notebook

Using a dataset provided by Airbnb, analysis and predictions will be made to understand what effects the total price of an Airbnb

• Updated Nov 8, 2022
• Jupyter Notebook

A machine learning model built to predict if a credit card application will get approved.

• Updated Sep 9, 2021
• Jupyter Notebook

Disaster response project that implements data engineering tactics to classify messages sent during a real-world disaster. This project uses ETL and ML pipelines and uses the Flask library to deploy the final result on a website.

• Updated Mar 7, 2026
• Python

Programming assignments covering fundamentals of machine learning and deep learning. These were completed as part of the Plaksha Tech Leaders Fellowship program.

• Updated Aug 7, 2021
• Jupyter Notebook

Building Machine Learning and ETL Pipelines to categorize emergency messages based on the needs communicated by the sender

• Updated Aug 28, 2021
• Python

RTA severity predictor is an application which predicts the severity of road traffic accident, so as to pave the way for improving the safety level of road traffic.

• Updated May 30, 2022
• Jupyter Notebook

Diabetes Prediction with Tree based models (Random Forest and XGBoost). Grid Search CV and Randomized Search CV used to optimize parameters

• Updated Jan 26, 2024
• Jupyter Notebook

• Updated Jun 11, 2021
• Jupyter Notebook

Bu projedeki amac bir sirketin kisa vadeli borclarini odeyebilme kapasitesini gosteren metrigin asagida aciklanmis belirli bagimsiz degiskenlere gore bir dogrusal regresyon modeliyle tahmin edilmesidir.

• Updated Jul 18, 2025
• Jupyter Notebook

In the digital music era, understanding artist popularity on Spotify is vital. This project taps into Spotify's data, analyzing key factors driving artist prominence. Through our insights, we illuminate what sets successful artists apart in this dynamic platform.

• Updated Aug 16, 2023
• Jupyter Notebook

Prepare a model for glass classification using KNN and Implement a KNN model to classify the animals in to categorie.

• Updated Feb 3, 2023
• Jupyter Notebook

Use decision trees to prepare a model on fraud data. Treating those who have taxable income <= 30000 as "Risky" and others are "Good" and A cloth manufacturing company is interested to know about the segment or attributes causes high sale.

• Updated Feb 4, 2023
• Jupyter Notebook

The "Potential Customers Prediction" project uses machine learning to predict which customers are likely to make a purchase. It involves data cleaning, exploratory analysis, and building models to identify potential buyers based on demographics and behavior. The model's performance is evaluated using metrics like accuracy and precision.

• Updated Sep 14, 2024
• HTML

Identify the most efficient machine learning model to identify potential donors. Project covers Linear Regression, Perceptron Algorithm, Decision Trees, Naive Bayes, Support Vector Machines and Ensemble Methods.

• Updated Mar 18, 2021
• HTML