oktaykurt

anomaly-detection-with-DBSCAN-and-LOF

Depth analysis of a dataset related to hypothyroidism, focusing on anomaly detection using unsupervised learning techniques. The analysis includes data preprocessing, visualization, and the implementation of DBSCAN, Local Outlier Factor (LOF), and a combined method of both.

chain-registry

chasm-inference-scout-setup-guide

This guide provides detailed instructions on setting up and running the Chasm Inference Scout, a tool that executes inference tasks assigned by Chasm's Orchestrator. By running the Inference Scout on your server, you can leverage powerful language models and contribute to the Chasm Network.

food-recognition-using-SIFT-BoW-with-traditional-classifiers

Implementation of a traditional machine learning approach using Scale-Invariant Feature Transform (SIFT) and Bag of Words (BoW) representation with Support Vector Machines (SVM) for food recognition. The dataset used for this project is the iFood-2019-FGVC6 dataset, which comprises 251 food classes.

human-activity-recognition

Classifying human activities using data collected from smartphone sensors. The main components are data preprocessing, feature analysis, model training, and evaluation. The project includes scripts for data preparation, model training, and a Streamlit dashboard for model evaluation.

price-prediction-with-machine-learning

This repository contains machine learning models for predicting prices using various machine learning techniques.

setting-up-a-celestia-light-node-for-mainnet-beta

This guide will walk you through setting up a Celestia light node on the Mainnet Beta, enabling you to perform data availability sampling (DAS) on Celestia's data availability (DA) network.

oktaykurt/chasm-inference-scout-setup-guide

This guide provides detailed instructions on setting up and running the Chasm Inference Scout, a tool that executes inference tasks assigned by Chasm's Orchestrator. By running the Inference Scout on your server, you can leverage powerful language models and contribute to the Chasm Network.

oktaykurt/anomaly-detection-with-DBSCAN-and-LOF

Depth analysis of a dataset related to hypothyroidism, focusing on anomaly detection using unsupervised learning techniques. The analysis includes data preprocessing, visualization, and the implementation of DBSCAN, Local Outlier Factor (LOF), and a combined method of both.

oktaykurt/chain-registry

oktaykurt/eigenlayer-KurtNode

oktaykurt/exercise-form-ai

oktaykurt/food-recognition-using-SIFT-BoW-with-traditional-classifiers

Implementation of a traditional machine learning approach using Scale-Invariant Feature Transform (SIFT) and Bag of Words (BoW) representation with Support Vector Machines (SVM) for food recognition. The dataset used for this project is the iFood-2019-FGVC6 dataset, which comprises 251 food classes.

oktaykurt/fuel-project

oktaykurt/hardhat-fund-me-fcc

Fund Me Contract - Learning from FCC & Patrick about Smart Contracts

oktaykurt/hardhat-web3-wallet

oktaykurt/human-activity-recognition

Classifying human activities using data collected from smartphone sensors. The main components are data preprocessing, feature analysis, model training, and evaluation. The project includes scripts for data preparation, model training, and a Streamlit dashboard for model evaluation.

oktaykurt/kepler-fill-and-submit-CRN

Kepler automation script for trying CRN values in given time intervals.

oktaykurt/price-prediction-with-machine-learning

This repository contains machine learning models for predicting prices using various machine learning techniques.

oktaykurt/setting-up-a-celestia-light-node-for-mainnet-beta

This guide will walk you through setting up a Celestia light node on the Mainnet Beta, enabling you to perform data availability sampling (DAS) on Celestia's data availability (DA) network.

oktaykurt/web3-lottery

oktaykurt/mainnet-testnet-bridge

oktaykurt/partisia-blockchain-example-contracts

oktaykurt/solidity-examples

example contracts

oktaykurt/Templates