This repository contains systems-oriented technical projects focused on machine learning, software validation, data visualization, predictive modeling, analytical diagnostics, and engineering-driven evaluation methodologies. The work emphasizes verification and validation (V&V), reliability analysis, comparative experimentation, reproducibility, and evidence-backed technical interpretation across software and data-centric systems.
The projects collectively demonstrate:
- Systems thinking and analytical problem solving
- Software reliability and validation workflows
- Machine learning evaluation and diagnostic analysis
- Quantitative modeling and visualization
- Structured experimentation and technical reporting
- Engineering-focused implementation practices
Comparative machine learning reliability analysis using poker hand classification data with emphasis on feature representation, model validation, diagnostic confusion matrix analysis, and evidence-backed evaluation across multiple supervised learning architectures.
Key Areas:
- AI/ML Reliability
- Classification Diagnostics
- Comparative Model Evaluation
- Validation and Performance Analysis
Dimensionality reduction and classification visualization study using the Iris and Indian Pines hyperspectral datasets with emphasis on PCA/LDA projection analysis, class separability evaluation, and multidimensional data interpretation.
Key Areas:
- Signal and Data Analysis
- Dimensionality Reduction
- Classification Visualization
- Hyperspectral Data Interpretation
Comparative predictive modeling study evaluating Support Vector Regression (SVR) and Artificial Neural Networks (ANNs) using automotive efficiency data with emphasis on validation, diagnostics, convergence behavior, and quantitative performance assessment.
Key Areas:
- Predictive Modeling
- Regression Analysis
- Model Validation
- Diagnostic Visualization
Systems-focused technical postmortem analyzing architecture, implementation decisions, system behavior, and operational outcomes within an interactive software environment.
Key Areas:
- Systems Analysis
- Software Architecture
- Technical Documentation
- Failure and Behavior Evaluation
Structured usability and workflow analysis evaluating user interaction patterns, interface effectiveness, and requirement alignment within a tuition calculator application.
Key Areas:
- Human-System Interaction
- Requirements Alignment
- Workflow Evaluation
- Usability Analysis
Statistical visualization and regression analysis study using the Iris dataset with emphasis on feature correlation analysis, predictive modeling interpretation, RMSE evaluation, and analytical data visualization.
Key Areas:
- Statistical Analysis
- Predictive Modeling
- Feature Visualization
- Regression Evaluation
Foundational multivariable regression study evaluating feature normalization techniques, optimization behavior, and predictive performance stability across structured datasets.
Key Areas:
- Multivariable Regression
- Feature Engineering
- Data Normalization
- Predictive Analytics
Foundational classification implementation exploring probability-driven prediction, decision boundary behavior, and supervised learning workflows using logistic regression methodologies.
Key Areas:
- Classification Systems
- Predictive Analytics
- Supervised Learning
- Decision Modeling
Foundational machine learning implementation focused on gradient descent optimization, iterative parameter convergence, and regression-based predictive modeling from first principles.
Key Areas:
- Optimization Algorithms
- Gradient Descent
- Regression Modeling
- Machine Learning Foundations
- Verification & Validation (V&V)
- Software Reliability and Diagnostics
- Machine Learning and Predictive Analytics
- Data Visualization and Interpretation
- Systems Analysis and Technical Evaluation
- Statistical Modeling and Classification
- Quantitative Performance Assessment
- Engineering Documentation and Reporting
technical-projects/
├── Resume/
└── TechnicalProjects/
├── AutoMPG_SVR-vs-ANN_ModelValidation/
├── MachineLearning_Foundations/
│ ├── LinearRegression_GradientDescent/
│ ├── LogisticRegression_Classification/
│ └── MultivariateRegression_FeatureNormalization/
│
├── MachineLearning_VisualizationDrivenModelAnalysis/
│ ├── IrisDataset_FeatureRelationshipVisualization/
│ └── IrisIndianPinesDataset_DataSeparationVisualization/
│
├── PokerHandClassification_AIModelReliabilityStudy/
├── UX_UsabilityStudy_TuitionCalculator/
└── War_GameSystems_Postmortem/