Featured Projects

Technical projects showcasing expertise in cloud security, data science, machine learning, and analytics.

Cloud Security & DevOps

Cloud Security Automation Platform

Enterprise-grade AI-driven security automation system for hybrid and multi-cloud environments. Integrates GCP, Terraform, ServiceNow workflows, and container security to provide real-time threat detection, automated compliance monitoring, and intelligent incident response.

60% reduction in incident response time • Automated compliance for 4+ business units • Zero security breaches post-deployment

Technologies Used:

Google Cloud Platform Terraform Kubernetes Python ServiceNow Docker CI/CD ML Models

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Data Science & Machine Learning

SpaceX Falcon 9 Launch Prediction

IBM Data Science Capstone project leveraging machine learning to predict SpaceX Falcon 9 first-stage landing success. Implemented exploratory data analysis, feature engineering, and multiple ML models including Logistic Regression, SVM, Decision Trees, and KNN with interactive Folium maps and Plotly dashboards.

92% prediction accuracy • Interactive visualization dashboard • Comprehensive EDA pipeline

Technologies Used:

Python Scikit-learn Pandas Folium Plotly Dash SQL Machine Learning

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Data Analytics & Economics

COVID-19 Global Economic Impact Analysis

Comprehensive data analysis project examining the economic ramifications of the COVID-19 pandemic on global markets. Analyzed GDP indicators, unemployment rates, and pandemic metrics across multiple countries to identify macro trends, recovery patterns, and policy effectiveness.

Analyzed 50+ countries • Identified 5 key recovery patterns • Published insights dashboard

Technologies Used:

Python Pandas Matplotlib Seaborn NumPy Statistical Analysis Data Visualization

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NLP & Social Media Analytics

Ukraine-Russia Conflict Sentiment Analysis

Natural Language Processing project analyzing Twitter sentiment during the Ukraine-Russia conflict. Implemented advanced text preprocessing, sentiment classification, and word cloud generation to visualize public opinion trends and emotional patterns in social media discourse.

100K+ tweets analyzed • Real-time sentiment tracking • Multi-language NLP pipeline

Technologies Used:

Python NLTK spaCy TextBlob WordCloud Pandas NLP Sentiment Analysis

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More Projects on GitHub

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