customer segmentation of insurance comapany

Convert a unstructured array into a stuctured dataframe.

Linear Regression Model on Airbnb prices of Seattle using Dash and Python

Learned to develop decision tree and random forest algorithms, incorporating hyperparameter tuning techniques such as random search and grid search

Attention Feature Fusion base on spatial-temporal Graph Convolutional Network（AFFGCN）

This repository is totally focused on Feature Engineering Concepts in detail, I hope you'll find it helpful.

This project will focus on data preparation and will follow the steps : data cleaning, handling text and categorical attributes, and feature scaling.

Explored the dataset of a company that specializes in the reselling of used and refurbished devices. The objective of this project was to determine the future price of used phones and identify the factors that significantly influence them using a linear regression model with python

Encoding: converting categorical data into a numerical data

Housing Price Prediction -Advanced regression techniques

DayCrew4 in 2023, Making PBL(Project based Learning) educational materials for beginners in data analysis.

Deep Learning -Artificial Neural Network

Skip-Gram Model From Scratch

A model for predicting the selling price of a used car using machine learning algorithms. This model is deployed in the Heroku Cloud Platform.

Advnace AI Course Mid Term Questions and Solution 2018

A program that will parse and encode a select column from a csv.

Deep Learning library.

This project aims to implement various word embedding methods.

A recommendation system created for H&M created with the help of EDA(Exploratory Data Analysis) and ALS (Alternative Least Squares) which optimizes a users recommendations taking into considerations an account`s view history and uses matrix optimization to give the best possible recommendations.

Kowalski knows everything about Tennis and Kowalski is never wrong. Kowalski uses a Deep Neural Network Framework to train intent based dataset. It uses One-Hot Encoding and CBOW concepts to further improve the results.

Implementing Semantic Segmentation on Satellite images using U-Net architecture

Feature Engineering on Time Series Dataset (Flight Price Prediction)

In this project we predict the forest cover type using the cartographic variables in the training/test datasets.

Bu projede Credit Risk Data veri setini kullanarak veri tipi dönüşümünü gerçekleştirdim.

Website to predict the prices of Real Estate.

Category transformation

Binary Classification Models with pySpark in Apache Spark