We compare model-free and model-based methods in the context of battery control.

e-Portfolio showcasing my personal projects.

Marmara Üniversitesi, Fen Bilimleri Enstitüsü, Bilgisayar Mühendisliği bölümünde sunulan “DERİN SİNİR AĞLARI İLE FEDERE ÖĞRENME TABANLI BİR KÖTÜ AMAÇLI YAZILIM TESPİT UYGULAMASI” başlıklı tez çalışmasına ait kaynak kodlarıdır.

The repository contains all the code for the paper amino acid encoding using deep learning application

This project uses a recurrent neural network (RNN) with Long Short-Term Memory (LSTM) layers to generate text based on Shakespeare's works. The model is trained on a subset of Shakespeare's text and can generate new text sequences based on the learned patterns.

Real-time, Multi-person & Multi-camera Fall Detector in Python

Project aims to forecast potato prices in India using LSTM, KNN, and Random Forest Regression, integrating historical data on prices, regional stats, and rainfall patterns. Targeting agricultural stakeholders for informed decision-making.

This project implements an Artificial Music Generator using LSTM (Long Short-Term Memory) networks, a type of recurrent neural network (RNN). The system generates music character by character based on a given input dataset.

Compare SVM mode yoga movement classification accuracy with Linear kernel, Polynomial kernel, RBF (Radial Basis Function) kernel, LSTM with accuracy up to 98%. In addition, it also supports adjusting the practitioner's movements according to standard movements.

Developing a PyTorch-based solution for predicting future values in financial time series data, leveraging RNNs and GRUs as part of the M3 competition for time series forecasting.

Stringlifier is on Opensource ML Library for detecting random strings in raw text. It can be used in sanitising logs, detecting accidentally exposed credentials and as a pre-processing step in unsupervised ML-based analysis of application text data.

End-2-end speech synthesis with recurrent neural networks

IEEE Transactions on Emerging Topics in Computational Intelligence

Learning parities with various neural network architectures

Pytorch based Neural Network Language Modeling (NNLM) Toolkit for easier and faster NNLM research and development. Result of my Master's Thesis work.

This repository includes a reinforcement learning framework for end-to-end type integrated thermal updraft localization and exploitation.

This is a Stock Prediction project in which i predict the stocks of Tata Steel Stock dataset (2015-2021). I used python and it's libraries to perform this project like Pandas, Numpy, sklearn etc. I used LSTM for predict prices of the stocks.

Neural Networks project for Intelligent Systems course at Tecnico, Lisbon.

Integrating Long-Short Term Memory to predict the Google Stock Market Price

Based on a Hybrid CNN-LSTM Network, an automated predicitve algorithm is constructed.