Browse Projects
Browse projects tagged with "AWS".
AWS Lambda & Amazon Bedrock: Benchmarking TF-IDF, LSTM, and Zero-Shot LLM Sentiment Analysis
Ai-mlA full ML pipeline benchmarking TF-IDF + Logistic Regression, a Keras LSTM, and Claude Haiku via Amazon Bedrock on 50,000 IMDb reviews. The winning model is deployed live as a serverless REST API on AWS Lambda with a Flask frontend.
LLM Document Summarizer — LLMOps with Amazon Bedrock
Ai-mlPDF document summarizer using Amazon Bedrock (Claude Haiku) with production LLMOps patterns: versioned YAML prompt templates, automated ROUGE evaluation, Bedrock Guardrails for PII redaction, and MLflow tracking of every inference call. Deployed on Azure App Service.
SMS Spam Classifier
Ai-mlSMS spam detection comparing three approaches — Naive Bayes, SVM, and Amazon Bedrock (Claude Haiku zero-shot) — on the same test set. Every prediction comes with a plain-English explanation of the words that drove it. Class imbalance addressed explicitly. Deployed on Azure App Service.
Stock Trend Pattern Recognition — Amazon SageMaker MLOps
Ai-mlStacked LSTM for stock trend pattern detection, served via Amazon SageMaker Real-Time Endpoint. Flask frontend on Azure App Service — multi-cloud MLOps. Pattern detection only, not financial advice.
Telco Customer Churn Predictor
DataChurn prediction with plain-language risk explanations a retention team can act on. Logistic Regression wins (ROC-AUC 0.8362), benchmarked against Amazon Bedrock Claude Haiku 4.5 zero-shot — tied at 70%. Flask API on Azure.
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