This repository implements a Temporal Convolutional Network (TCN) model for predicting financial instrument prices, including currencies, stocks, and cryptocurrencies. It uses advanced techniques like gradient boosting to improve prediction accuracy and handle diverse datasets effectively.
Multi-country energy price forecasting system with event awareness and data quality guards.
Open-source electricity spot price forecasting toolkit for China power markets.
Easy to follow stock price analysis on Indian stock data
Powerful XRP price forecasting using public data. Stacking ensemble (Bi-GRU/LSTM/CNN-LSTM + LightGBM/XGBoost, RidgeR). Fuses market OHLCV (CCXT), news sentiment & top50 whale activity. No API keys or signups. Easy setup. CPU/GPU-ready. Multi-horizon single run forecasting. Backtests + Predictions visuals: plot_charts & in-depth tensorboard dash
This project, I am constructing a predictive model that can prognosticate gold prices using historical price data and pertinent financial indicators.
EU power market model for system analysis
Enterprise AI Lab, encompassing AI scenarios utilized by various types of enterprises including finance, manufacturing, and energy, providing guidance for scenario
This repository contains an implementation of the LightGBM model for predicting financial instrument prices like stocks, currencies, and cryptocurrencies. It uses gradient boosting to analyze patterns in price data, aiming to enhance the accuracy and reliability of financial predictions.
AI-powered e-commerce competitor analysis with price forecasting (0.38% MAPE) and sentiment analysis using Chronos, Prophet, and Llama 3.3 70B
7-day-ahead wholesale crop price forecasting for Punjab, Pakistan β Playwright-scraped government market data, LightGBM benchmarked against a naive baseline, and a live Streamlit demo.
LLM crop advisor paired with LSTM price forecasting across 200 stations for Pakistan's agriculture sector.
β¨ Home Assignment for the Data Scientist Position (Curves) at Argus Media Group
Using Long-Short Term Memory Neural Networks to forecast and trade Ethereum, a cryptocurrency.
This repository implements a Random Forest Regressor for price prediction in financial markets, including stocks, currencies, and cryptocurrencies. It uses gradient boosting techniques to improve the model's accuracy and robustness for forecasting financial data across different datasets.
BevIntel AI is a tool which predicts beverage prices using real product attributes and market patterns, with models trained on cleaned and feature-engineered data. It focuses on identifying the key factors that drive pricing changes.
π Home Assignment for the Data Scientist Position (Curves) at Argus Media Group
Forecasting and trading framework for German day-ahead and intraday markets using EPEX Spot and ENTSO-e data. Extendable to other European markets. Potential for generation/load forecasting.
Developed a machine learning-based predictive model to forecast Airbnb prices using features like location, amenities, and property type.
This API service is used to forecast product price given the contributing materials that form the final product.
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