Body_Signals_of_Smoking – AWS-Terraform-testing

My background in flow cytometry and data analysis sparked my curiosity for technology and led me to complete a certification program in Data Science and Machine Learning. Since then, I have deepened my Cloud Engineering expertise with a focus on AWS services and infrastructure as code with Terraform.

My goal is to improve and master Cloud Engineer challenges; in “Body_Signals_of_Smoking – AWS-Terraform-testing” I demonstrate the deployment of a Data Science & Machine Learning project with Streamlit on AWS, including a web portal for smoker detection using biomarkers.

• Data Science & ML: Development of predictive models (Random Forest) with Scikit-Learn, including model evaluation (83% accuracy) and deployment of ML-APIs using Flask/Streamlit.
• Data Analysis & Visualization: Comprehensive EDA with Pandas/NumPy, creation of interactive dashboards (Streamlit) and visualization of trends (Matplotlib/Seaborn).
• Data Engineering & Cloud/MLops: Building end-to-end pipelines (cleaning with Python, feature engineering, cloud integration with AWS S3/RDS) and ML deployment with IaC (Terraform) on AWS (EC2, S3, RDS), with knowledge in MLOps.
• CI/CD & Automation: Optimization of CI/CD pipelines with GitHub Actions; automation of validation, deployment, and maintenance processes.

As a career changer with a passion for DS & ML, I am flexible and eager to apply my skills in practice.