A comprehensive guide for web developers to master DevOps practices in their workflow.
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Updated
Nov 2, 2023
A comprehensive guide for web developers to master DevOps practices in their workflow.
This is my Todo Fullstack Application made by ASP.NET Core 8 Web API for the backend, SQL Server for the DB and ReactTS for the frontend.
Desktop IDE to write and deploy serverless APIs to Cloudflare Workers, AWS Lambda@Edge, and Vercel Functions. Built with Electron, React, and TypeScript.
This is the Github repo for deployment files for the TodoFullstack project. you can see the deployed api from that link:
production ready implementation of Linear Regression using only NumPy, demonstrating the mathematical foundations from gradient descent to scalable deployment.
This is an End to End project designed to model a solution on Spain electricity shortfall challenges and make future prediction.
This repository details the data science workflow, feature engineering, and hyperparameter tuning process used to create the final King County Housing Price prediction model, resulting in FastAPI deployment.
Built a production-ready ML pipeline to predict USA used car auction prices. Features robust data engineering, hyperparameter optimization, and statistical validation, deployed via a FastAPI endpoint.
machine-learning mlops fastapi mlflow docker docker-compose model-registry experiment-tracking api-deployment monitoring production-system
Built a scikit-learn ML pipeline to automate IT ticket routing. Cleans raw data errors and accurately classifies text to direct requests to the correct department, resulting in FastAPI deployment.
A template project for packaging and deploying your Machine Learning model as a REST API.
Engineered an end-to-end ML pipeline to detect fraudulent job postings, handling a severe 95/5 class imbalance. Processed messy text and metadata to train a robust classification model, resulting in a deployed production API.
Enhance gaming experiences with our machine learning-based video game recommendation system. Using a content-based approach, our system suggests personalized game recommendations based on user preferences and game features. Explore our dataset, ETL process, NLP analysis, and the deployed API for interactive gaming insights.
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