M

machine learning

Armadillo: fast C++ library for linear algebra (matrix maths) & scientific computing - https://arma.sourceforge.net

Extract video representations (semantic, geometric, deep features) for the frames of any video.

A landcover classification tool based for humans. Classifier does "traditional" supervised and unsupervised learning. Image segmentation and soon also object detection

Instance Hardness analysis in Machine Learning

Genetics Algorithms and Genetic Programming library. https://genetics4j.org

This repo will have all resources, labs, data which I use/d on Kaggle Network

Graph-based Live Anomaly Detection on Semantic Streams

Bahn-Vorhersage - The best Train Delay Prediction System.

Este es mi primer repositorio.

Sashimi - study the organisation and evolution of corpora

Trading Bot – Algorithmic Crypto Trading with AI Integration

This project is a powerful algorithmic trading bot for cryptocurrency markets. It combines traditional technical analysis with modern machine learning to generate accurate and intelligent trading decisions.

Key Features:

Candlestick Pattern Detection: Identifies classic reversal patterns such as Hammer, Doji, Engulfing, Shooting Star, and complex formations like triangle patterns.

Technical Indicators: Includes standard indicators (RSI, MACD, Moving Averages, Bollinger Bands) and advanced tools like Ichimoku Clouds, SuperTrend, Fibonacci Retracements, and more.

Machine Learning Integration: Uses LSTM-based models for time-series forecasting and momentum strategies, combined with indicator signals through weighted evaluation.

Dynamic Signal Weighting: Customizable signal weighting for patterns, indicators, and ML predictions with automatic adjustments to market volatility.

Trade Execution Engine: Supports long/short positions with stop-loss, take-profit, and trailing stop features. Automatically includes fees and tax deductions in profit calculations.

Backtesting & Debugging: Simulates strategies on historical data with detailed equity/value curve visualization and comprehensive debug logs.

Robust Error Handling: Detects and logs data inconsistencies, index errors, and processing issues to ensure stability.

Modular architecture with key components such as TraderBot, SignalHandler, PatternManager, IndicatorManager, MLModelHandler, SequenceManager, DataAPI, and CryptoCurrency. Additional support provided by PatternCalculator, IndicatorCalculator, and DataProcessing.

Version: V1.3.0.0 | GUI: V1.0.0 Author: Marian Seeger – info@seegersoftwaredevelopment.de

Implementation of Association Rule Mining concept in Machine Learning, which is used for applications in Data Mining

Homework code for assignment 3 : K-Means Clustering

An extension to the agent-based electricity market model AMIRIS providing external electricity price forecasts

This package provides a modular framework for the semi-automated processing of entomological specimen labels. It uses artificial intelligence to perform label detection, classification, rotation correction, OCR, and clustering laying the groundwork for comprehensive information extraction. It is designed to work in conjunction with the python-mfnb package for downstream clustering tasks.