MlFlow Project creating pipelines and using Grid-Search Cross Validation to find optimal parameters for Old School Runescape Machine Learning datasets.

Marketing Data Analysis Project

Built Random Forest classifier from scratch on top of Scikit Learn decision trees. Using Scikit Learn to create data cleaning pipelines, perform grid searches for hyper parameter tuning, and decision tree modeling

Classification of fetal cardiotocography to determine whether pattern is normal, suspect or pathalogical.

A Machine Learning Model built in scikit-learn using Support Vector Regressors, Ensemble modeling with Gradient Boost Regressor and Grid Search Cross Validation.

Retail data analysis using machine learning techniques in Python and Sklearn packages to help Ugly Christmas Party determine how many sweaters to order for each ugly Christmas sweater design created.

GridSearchCV For Model optimization

This repository contains all the work projects carried out with respect to learning and experiments on Big Data Analytics. The scripts are formed to build machine learning models for future predictions.

Applied Machine Learning ( End to End ) Classification Models

Data in the social networking services is increasing day by day. So, there is heavy requirement to study the highly dynamic behavior of the users towards these services. The task here is to estimate the comment count that a post is expected to receive in next few(H) hours. Data has been scraped from one of the most popular social networking site…

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

I leveraged an algorithmic approach for document classification and document clustering. Various models have been trained for document classification and they all have been evaluated using performance metrics followed by tuning of the model hyper-parameters to reach the most accurate classification. Additionally, a model has been trained for doc…

This repo contains all machine learning algorithms using python and scikit-learn

The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidate…

Machine Learning with Python

Text Mining Competition

This project is made for search the best regression model based in some metrics training some models and evaluating them

A simple implementation of the Logistic Regression Classifier on the Breast Cancer Dataset with L1 regularization and GridSearch for hyperparameter tuning.