AI & Machine Learning over historical baseball data using latest Microsoft AI & .NET Development Technologies
- blazor
- machine-learning
- artificial-intelligence
- baseball-statistics
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AI & Machine Learning over historical baseball data using latest Microsoft AI & .NET Development Technologies
nengi+babylon template of a 3d shooter with client-side prediction and lag compensation
The Scenario Architect provides a lightweight graphical user interface that allows a straightforward realization and manipulation of concrete driving testing scenarios. Exemplary usecases are the validation of an online verification framework or training of an prediction algorithm.
🌅 iOS11 demo application for visual sentiment prediction.
PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"
Nova DSO Tracker is an open-source Flask application for astrophotographers, providing real-time tracking of deep-sky objects' altitude, observability prediction, and integration with Stellarium and SIMBAD databases.
Satellite prediction library for crystal using the sgp4 model
The application allows you to trade on the outcomes of events, and follow the odds to garner accurate insights about the future. Users buy or sell Voting Shares, which can be redeemed for 1 unit of the stable asset if the outcome is resolved as correct, and become worthless if it’s incorrect.
Stock price prediction using a deterministic algorithm inspired by LSTM, focusing on pattern recognition in historical data.
Wisp CLI — Interactive trading platform for backtesting and live trading across spot, perpetual futures, options, and prediction markets
Open BTC 5-minute prediction market sandbox for AI agents — register with one API call, get 1,000 test credits, and place a live order
Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.
Package to set up autonomous agents to trade on TBD
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.
GNN-based gene-selection deep learning model for drug response prediction