100 Days of System Design Road map for DevOps Engineers to enhance their skills with resources and step by step blogs

An end-to-end data pipeline that transforms raw, unstructured customer support tickets into actionable business insights. Using Python and the Groq API (Llama 3.1), the system automatically extracts churn risk and categorizes issues, storing the structured data in PostgreSQL for advanced analytical querying. The project culminates in an interactive

This is and end-to-end project using the AdventureWorksDW2019 database for my report. In this report I analyze important statistics based on the Internel Sales & Providing an overview of the current inventory status and making forecast.

Built a real-world email spam classifier using Support Vector Machine(SVM), achieving 98% accuracy through robust text preprocessing, TF-IDF feature extraction, and EDA. Deployed the model with Flask, enabling real-time predictions and visualization of words influencing classification.