time-series-data

Python Streaming DataFrames for Kafka

Python framework to manage time series structured as one-level dictionaries.

Python framework to manage time series

Tool for creating and managing waveforms to prepare fusion pulses

Python package for accessing real-time and historical data on industrial historians and control systems.

We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for produce an anomaly score. Then, we merge these two score and produce merged anomaly score as a result.

An autonomous quantitative trading architecture powered by a proprietary Triple-Node Consensus engine. It merges high-speed technical mathematics, Groq LLM sentiment analysis, and PgVector RAG-embedded SEC filings to validate market setups, autonomously executing risk-managed bracket orders via the Alpaca API with immutable audit logging.

😁 historical options pipeline

Official repository for the ParDeeB framework and the Shahrekord Energy Dataset: A high-resolution 4-year hourly benchmark (30,000+ samples) featuring 23 meteorological and temporal determinants for short-term load forecasting.

Automated Time Series Feature Engineering

A single-node data lakehouse for quantitative research that ingests market data, normalizes it into point-in-time safe datasets, and produces analysis-ready features for backtesting and modeling using Python, Parquet, and DuckDB

This is an educational project designed for students: an interactive analytical dashboard built with Dash and Plotly, allowing users to explore automobile sales trends in the United States from 1980 to 2023. The project demonstrates key skills in Python code structuring, modular application architecture, data visualization, unit testing, and CI/CD

Application implemented in C++ which measures time-series data for soil-based instruments and provides serial usb interface for other devices

Semester project for my Machine Learning course: Classification of human motion through custom time series positional data shapelet transformations.

Creating function to visualize time series data. The dataset contains the number of page views each day on the freeCodeCamp.org forum from 2016-05-09 to 2019-12-03.

Data scraping and analysis pipeline for Aviator game odds. Includes statistical exploration and LSTM-based prediction model trained on 15,000+ rounds.

High-throughput, Rust-accelerated temporal join engine for quantitative finance ML pipelines. Engineered via PyO3 to eliminate look-ahead bias and accelerate point-in-time feature generation on massive time-series market datasets

Stock Price Predictor is a machine learning project that predicts stock closing prices using historical data. It uses Random Forest Regression, supports multiple stocks, and features an interactive Streamlit web app. The project demonstrates an end-to-end ML pipeline from data collection to deployment.

Application implemented in Python which pulls time-series data and upload it to an API web-service