Projects with this topic
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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
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AWS graduation project: Auto-scaling Flask application with Terraform IaC and GitLab CI/CD pipeline
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Teenage Mutant Ninja Turtles: Flask Web App. Cowabunga!
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A Flask API for a DEPT challenge for a back end position
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Code base for the AndBiodiversity BIOHME application and database
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App Name: NewsHub
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O projeto consiste no desenvolvimento de uma API back-end utilizando Python com a biblioteca Flask. A API REST atua como interface de comunicação entre o aplicativo mobile, gerenciando e controlando as requisições recebidas do aplicativo para garantir uma integração eficiente e menos complexa entre as aplicações.
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API construída em Python para realizar reconhecimento facial de uma imagem e comparar com outras imagens armazenadas em um banco de dados Mongodb, e retornar se é a mesma pessoa. Serviços do projeto foram feitos em docker com containers para a api e o mongo.
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A basic "front-end" microservice written in the python Flask framework that merely returns some environmental variables from kubernetes. It is intended to be a proof-of-concept.
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This project is made to demonstrate a working CI/CD pipeline. From python webapp development, to unit testing and SonarQube, to building container image to AWS Elastic Kubernetes cluster
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My own personal website, includes a blog, about me section with all my experience and a projects page
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Es un ejemplo sencillo de un API REST en Python + Flask. Contiene un Dockerfile para crear una imagen del proyecto, y un Docker Compose para desplegar todo el proyecto.
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Project used for our Annual Project work as a runner for our game.
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Git Migration App - is a tool for an automated cloning of any given repository from any remote to your Gitea server.
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Web app for scatter plot surveys and check-ins
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ToDo Hive is a Flask-based web application that allows users to manage their todos. It includes features such as user authentication, adding, editing, completing and reopening todos. Frontend is written in german.
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