A pipeline to CI/CD of a machine learning model on Google Cloud Run
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Updated
May 1, 2023 - Python
A pipeline to CI/CD of a machine learning model on Google Cloud Run
This script uses Python and Redis with Twitter API to run a fully automated twitter account.
This repository accompanies the freeCodeCamp guide, “How to Deploy Your FastAPI + PostgreSQL App on Render: A Beginner’s Guide” by Preston Osoro. It provides a hands-on example of building and deploying a modular FastAPI backend integrated with PostgreSQL, using Render’s free-tier cloud services.
🏠 Real estate application AWS, GCP and Azure + Terraform
Full-stack web applications development & deployment tool for AWS Elastic Beanstalk and Google App Engine
A full-stack Job Board web app built with Django and PostgreSQL (Supabase). Employers can post/manage jobs, and applicants can browse and apply with resumes, cover letters, and portfolio links. Deployed on Render.
Welcome to MoodMate repository! This project features an interactive chatbot designed to offer empathetic responses and basic emotional support. Through thoughtful conversational design, MoodMate provides a comforting and engaging experience, helping users feel heard and understood.
Python / Automation – Automates job scraping by keyword and location, filters duplicates, and emails listings daily. Python scripting, web scraping, scheduling, and data pipeline development.
🤖 基于Kook平台的智能抖音视频下载机器人 | 自动检测抖音链接,下载视频和封面图片到Kook | 支持多链接备用、随机请求头、智能去重 | Python异步处理 | 推荐DigitalOcean部署
A full-stack data management system for automating the ingestion, storage, and reporting of physiological test data. Built with Streamlit, MongoDB, and AWS (EC2/S3), the app replaces manual Excel workflows with secure cloud-based visualizations and PDF reporting tools.
FastAPI backend to handle the university base management system. This aims to manage the student attendance and other relevant functionalities.
Cloud-native order fulfillment system built with Python and Flask, using AWS, Docker, and Terraform.
🧠 End-to-End Phishing Website Detection using Machine Learning and MLOps — A scalable Flask-based system with automated data pipelines, MLflow experiment tracking, DVC versioning, Dockerized deployment on AWS (EC2, ECR, S3), and CI/CD via GitHub Actions & DagsHub.
An enterprise-grade, full-stack AI travel planner which provides data-driven itineraries for Lucknow, India and showcases production-ready architecture, combining a FastAPI backend with a Streamlit frontend. It leverages an advanced agentic RAG system, context-aware responses by integrating a local knowledge base with live, external APIs.
PerfectPick is an AI-powered smartphone recommendation system built with Flask and Postgres for session management, AstraDB for vector storage, and hybrid retrieval using BM25 and BGE embeddings. Deployed on GCP with Docker and Kubernetes, integrated with Prometheus and Grafana for scalable, production-grade performance and MLOps observability.
A tool for Business Development Officers to automate outreach email generation based on job descriptions. Uses LangChain for web scraping, LLaMA 3.1 on Groq for NLP tasks, and ChromaDB for vector database queries, making client outreach faster and more efficient.
The personalised healthcare system uses machine learning to provide tailored treatment recommendations based on patient data. It analyzes medical history and lifestyle factors to predict health risks and suggest preventive care. The system enhances patient outcomes through data-driven insights.
🛠️ Create and execute shellcode payloads effortlessly using ASPxecute and `aspnet_compiler.exe` for seamless integration on Windows and Linux environments.
Interactive Streamlit web app for analyzing NYC Airbnb listings with comprehensive EDA, pricing insights, geographic visualizations, and market trends analysis
The financial data analytics and forecasting model analyzes historical financial data to predict future trends and market movements. It uses machine learning algorithms and time series analysis to provide insights for informed decision-making. The model helps improve financial planning and risk management.
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