Projects

The ObjectDetector project is designed to identify and classify objects in images and videos using advanced deep learning models such as Faster R-CNN and YOLO (You Only Look Once).

The NewsClassifier project is a machine learning system designed to classify news articles into distinct categories such as sports, politics, technology, and more.

The goal of the FaceAI project was to develop a face recognition system leveraging Convolutional Neural Networks (CNNs).

The EmotionVision project is an innovative exploration into teaching machines to recognize human emotions from facial images.

The SupplyForecast project focuses on predicting product demand in supply chains.

This project, Cluster Market, is designed to segment customers based on their purchasing behavior and characteristics using k-means clustering.

The SmartChatbot project is aimed at developing an intelligent chatbot capable of answering user queries and enhancing the user experience in automated communications.

The Churn Predictor project aimed to forecast customer churn using a machine learning approach.

The objective of PDF Chatbot project was to develop an Artificial Intelligence chatbot capable of interacting with the content of a book provided in PDF format.

My AI Business Chatbot project focused on creating an AI-powered chatbot to assist business owners in learning detailed information about their operations and micro-managing various aspects of their businesses using their own databases.

The Stock Predict project in Data Science aims to forecast stock or asset prices using advanced time series models like ARIMA, Prophet, or LSTM.

The idea to write the SAS2py project started when the migration from SAS to Python seemed necessary.

1. Human Classification (Part 1)Finally, it has been 20 days since we started developing a product that our colleagues in the R&D department have been working on for a long time.
2. Human Classification (Part 2) These three phases are as followsAs a result, this project has three main phases, each with many details that we will explain in detail.
3. HumanClassification (Part 3) – Parsing the pageIn this phase, we’ve planned to parse the given page to obtain some essential data.

Analyzing the problems identified by Google Lighthouse can help us understand what improvements our site needs.

To build an AI model that can address the issues identified by Lighthouse, we need appropriate data.