Projects with this topic
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The main project for OctoMY™ - Ready-to-run robot software
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🤖 AI browser extensions & userscripts to augment your web experienceUpdated -
fadliwiryawirawan CYBERW1RY4-LAB / microsoft_googleplex
CI/CD Catalog (unpublished)aktivasi microsoft dalam pengembangan LTS maupun windows worit globally https://github.com/cyber-vivo-w1ry4/Topics-Unity-/forks https://github.com/cyber-vivo-w1ry4/mirosoft-Botnet/forks https://github.com/cyber-vivo-w1ry4/cpp/forks https://github.com/cyber-vivo-w1ry4/python/forks https://github.com/cyber-vivo-w1ry4/Google-Antigrafity https://github.com/cyber-vivo-w1ry4/CyberSecurity/forks https://github.com/cyber-vivo-w1ry4/Topics-windows-/forks https://github.com/cyber-vivo-w1ry4/cyberw1ry4-LAB/forks https://github.com/cyber-vivo-w1ry4/cyberw1ry4-Payment-ecommerce-moneychanger/forks
Linux C++ Android game C API Bash GitLab Go Rust Ansible C# python3 AI nodejs website web golang hacktoberfest Terraform Django Kubernetes cli Amazon Web S... Node.js bot dotfiles Git MySQL Kotlin Angular Laravel library PostgreSQL Windows minecraft Flutter Unity JSON devops machine lear... plugin automation shell MongoDB js Ruby shishifubing Archived documentation Spring Vue.js discord Qt bootstrap html5 arduino llm blog debian legend REST API LaTeX Program gui Markdown docker-compose theme Lua Express app venice-ai frontend security template ci privacy WordPress PHP TypeScript CSS HTML Docker React JavaScript Python CSV parquet Java openml dataset datagit server tabular flask gitlab-ci vue node site-scribou... spring boot android-app open-source Google Maps API Google Cloud... cyberattack hacktivies community Reddit bot chatgpt-apiUpdated -
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Bandicoot: user-friendly C++ library for GPU accelerated linear algebra, integrating with CUDA, OpenCL, Vulkan
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Bahn-Vorhersage - The best Train Delay Prediction System.
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Hybrid cloud-edge ML system for predictive rain control with automated retraining, monitoring, and Raspberry Pi hardware actuation.
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Armadillo: fast C++ library for linear algebra (matrix maths) & scientific computing - https://arma.sourceforge.net
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test123=123 test:test123 dataset openml datagit tabular parquet CSV Python JavaScript Java Docker HTML CSS Linux React PHP C++ TypeScript Android game Rust Go GitLab C Ansible API Bash python3 C# nodejs website web golang hacktoberfest Django bot Terraform dotfiles Kubernetes Angular MySQL cli Node.js Kotlin Laravel library Git Amazon Web S... PostgreSQL Windows Unity JSON WordPress Archived shishifubing js devops Ruby plugin shell MongoDB template bootstrap security AI discord automation html5 Spring Qt arduino blog documentation Vue.js Program LaTeX theme gui REST API machine lear... Express legend app ci vue Markdown flask node server docker-compose spring boot Flutter Lua debian in preparation iOS hugo vim R CSS3 minecraft trololoUpdated
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A landcover classification tool based for humans. Classifier does "traditional" supervised and unsupervised learning. Image segmentation and soon also object detection
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Apex est un panel moderne de gestion et d'administration conçu pour offrir une expérience rapide, légère, sécurisée et hautement évolutive. Le projet a pour objectif de proposer une alternative professionnelle aux panels traditionnels en plaçant la performance, la modularité et la maintenabilité au centre de son architecture.
Apex repose sur une architecture distribuée composée de trois couches principales. Le cœur du système est développé en Rust afin de bénéficier de performances élevées, d'une gestion fine des ressources et d'une excellente sûreté mémoire. Une Gateway développée en Go constitue l'intermédiaire entre le cœur du système et les clients. Elle centralise notamment l'API publique, l'authentification, la gestion des sessions, les communications temps réel et la validation des requêtes. L'interface utilisateur est développée en TypeScript avec React et Vite, accompagnée de SCSS, afin de fournir une interface moderne, réactive et légère.
La gestion des conteneurs repose sur containerd. Cette approche permet à Apex de contrôler précisément son environnement d'exécution tout en conservant une séparation claire entre la logique métier et l'infrastructure.
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Materials on various sections in Computer Science (CS).
🎓 с с++ shell Bash makefile Git GitLab github SQL computer sci... PowerShell Mobile Devel... Android iOS devops game develop... Web Development JavaScript Java Python Docker HTML CSS TypeScript C++ Rust game Go C C# python3 nodejs golang Django Node.js MySQL Kotlin Windows PostgreSQL Flutter machine lear... js Ruby Qt Markdown R Swift cybersecurity Cyber Security bioinformatics deep learning big data NumPy pandas matplotlib scikit-learn scipy development softwareUpdated -
Predicting 30-Day Hospital Readmission in Diabetic Patients
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$ mldev | is a data science experiment automation and reproducibility toolkit.
check our experiment templates: https://gitlab.com/mlrep
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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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Alex4M9_ARMG0268XZ59
My personal portfolio, website, shop, platform everything in one.
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Hybrid Filtering with Spark MLlib
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💬 Epic prompts to turbo-charge your LLM chatbots.Updated
