GitHub - uma1r111/MLOps-AQI-Project: End-to-End AQI Forecasting — A fully serverless MLOps project leveraging AWS (Lambda, S3, EventBridge, Step Functions) with Jenkins CI/CD, Prometheus & Grafana monitoring, and Evidently AI for drift detection. Iterative optimization using DVC, MLflow, and BentoML for reproducible experiments, controlled testing, and scalable API deployment.

Name		Name	Last commit message	Last commit date
Latest commit History 1,070 Commits
.dvc		.dvc
.github/workflows		.github/workflows
Data Collection		Data Collection
Data Preprocessing		Data Preprocessing
Data		Data
Exploratory Visualization Analysis		Exploratory Visualization Analysis
Exporter		Exporter
Feature Selection		Feature Selection
Model Serving		Model Serving
Model Training		Model Training
Prediction Client		Prediction Client
streamlit_app		streamlit_app
.dvcignore		.dvcignore
.gitignore		.gitignore
Jenkinsfile		Jenkinsfile
README.md		README.md
bentoml_forecast_output.csv		bentoml_forecast_output.csv
feature_selection.csv.dvc		feature_selection.csv.dvc
fetch_daily_data.py		fetch_daily_data.py
full_preprocessed_aqi_weather_data_with_all_features.csv		full_preprocessed_aqi_weather_data_with_all_features.csv
karachi_weather_apr1_to_current.csv		karachi_weather_apr1_to_current.csv
metrics.json		metrics.json
predictions.csv.dvc		predictions.csv.dvc
requirements.txt		requirements.txt

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