Emre Ates's Projects
Armut, Turkey's largest online service platform, connects service providers with customers looking for services such as cleaning, renovation, and transportation. Armut aims to create a product recommendation system using Association Rule Learning based on customer service usage and categories.
This project aims to predict if a cancer diagnosis is benign or malignant using Support Vector Machine (SVM) model. The model utilizes several features related to cancer cells to make predictions.
A retail company wants to create a roadmap for its sales and marketing activities. To plan for the medium to long term, the company needs to predict the potential value that existing customers will bring in the future.
This project involves comparing the effectiveness of two bidding methods, "maximum bidding" and "average bidding," through an A/B test. The goal is to determine whether the "average bidding" method yields more conversions compared to the existing "maximum bidding" method.
The goal of this project is to build a content-based movie recommender system. The system provides movie recommendations to users based on the content and descriptions of movies they have shown interest in.
This project aims to inspire users by sharing recipes that they can make with the ingredients they have, or according to the category and/or cuisine they choose.
This project aims to perform customer segmentation and revenue prediction for a gaming company based on customer attributes. The company wants to create persona-based customer definitions and segment customers based on these personas to estimate how much potential customers can generate in revenue.
This project involves performing customer segmentation and RFM (Recency, Frequency, Monetary) analysis on customer data from a retail company. The primary goal is to categorize customers into segments based on their buying behavior and identify potential target groups for marketing campaigns.
The primary goal of this project is to convert free users of a financial tracking app into paid members. This conversion will be achieved by building a model that identifies users who are unlikely to enroll in the paid version of the app.
This project aims to create a deep learning model for classifying fashion items using the Fashion MNIST dataset. Below, you can find the steps of the project and the results obtained.
You decide it's best to automate the game night selector to get the most people through the door.
The goal of this project is to implement a Hybrid Recommender System that combines item-based and user-based recommendation methods to provide movie recommendations for a specific user. The system aims to offer a total of 10 movie recommendations by using both methods.
This project focuses on solving two key problems in e-commerce: accurately calculating ratings for products based on recent reviews and sorting reviews effectively. Solving these problems can lead to improved customer satisfaction, increased product visibility for sellers, and a seamless shopping experience for buyers.
Config files for my GitHub profile.
By examining the products that customers purchase together, we will provide recommendations to similar shoppers. This is a data mining approach that can be used to enhance customer satisfaction and increase sales.
This is a Python project for tracking and calculating scores in a game of Scrabble among friends. The project uses dictionaries to organize players, words, and points.
This is a Python program that can decode secret messages encoded using different ciphers. The program currently supports two ciphers: a simple Caesar cipher and a Vigenère cipher.
This Python project includes functions for calculating shipping costs, driver costs, and money earned from trips using the Nile service.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent