https://github.com/bpavan16/aps-portfolio
This project is a portfolio website showcasing the application of Data Structures and Algorithms (DSA) in solving real-world problems, with a focus on Amazon's Ecosystem
https://github.com/bpavan16/aps-portfolio
algorithm-design-and-analysis amazon coursework-project data-structure-design portfolio-website
Last synced: 4 months ago
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This project is a portfolio website showcasing the application of Data Structures and Algorithms (DSA) in solving real-world problems, with a focus on Amazon's Ecosystem
- Host: GitHub
- URL: https://github.com/bpavan16/aps-portfolio
- Owner: bPavan16
- Created: 2025-04-18T14:52:46.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-08T15:57:52.000Z (12 months ago)
- Last Synced: 2025-09-07T10:34:26.765Z (9 months ago)
- Topics: algorithm-design-and-analysis, amazon, coursework-project, data-structure-design, portfolio-website
- Language: HTML
- Homepage: https://bpavan16.github.io/aps-portfolio/
- Size: 2.61 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Amazon Algorithm Analysis Portfolio
A comprehensive case study portfolio analyzing how Amazon leverages advanced algorithms and data structures to power its global e-commerce and cloud computing infrastructure.
## šÆ Project Overview
This project presents 19 detailed case studies examining the algorithmic foundations behind Amazon's operations, from string processing for Kindle search to distributed systems for AWS. Each case study demonstrates practical applications of computer science theory in real-world, large-scale systems.
## šļø Project Structure
```
portfolio/
āāā index.html # Main portfolio homepage
āāā business-cases.html # Complete algorithm case studies
āāā references.html # Academic references and sources
āāā styles/
ā āāā style.css # Main styling
ā āāā style2.css # Additional components
ā āāā style4.css # Case study specific styles
ā āāā case-study-2.css # Extended case study styling
āāā scripts/
ā āāā script3.js # Interactive functionality
ā āāā navigation.js # Navigation handling
āāā images/
ā āāā lcs.png # Algorithm visualizations
ā āāā profile/ # Profile images
āāā README.md # Project documentation
```
## š Case Studies Included
### String Processing & Search
1. **Kindle Substring Search** - Suffix Trees for efficient text search
2. **Autocomplete System** - Trie data structures for real-time suggestions
3. **Product Matching** - Longest Common Subsequence for similarity detection
### Graph Algorithms & Optimization
4. **Route Optimization** - Dijkstra's and Bellman-Ford algorithms
5. **Seller Trust Ranking** - PageRank for reputation systems
6. **Package Delivery** - Hungarian Algorithm for optimal assignment
7. **Stable Matching** - Gale-Shapley for marketplace matching
8. **Traffic Management** - Ford-Fulkerson for network flow
9. **Fulfillment Network** - Minimum Spanning Trees for logistics
### Data Structures & Management
10. **Real-time Analytics** - Segment Trees for range queries
11. **Inventory Tracking** - Fenwick Trees for efficient updates
12. **Recommendation Cache** - LRU Cache for performance optimization
13. **Cart Management** - Stack for undo/redo functionality
14. **Warehouse Navigation** - A* Search for robot pathfinding
### Advanced Applications
15. **Clickstream Analytics** - Skip Lists for time-series data
16. **User Clustering** - Union-Find for community detection
17. **Media Compression** - Huffman Coding for streaming optimization
## š ļø Technologies Used
- **Frontend**: HTML5, CSS3, JavaScript (ES6+)
- **Styling**: Custom CSS with Flexbox/Grid layouts
- **Icons**: Font Awesome 6.0
- **Fonts**: Google Fonts (Poppins)
- **Responsive Design**: Mobile-first approach
## šØ Features
### Interactive Design
- **Responsive Layout**: Optimized for desktop, tablet, and mobile devices
- **Smooth Animations**: CSS transitions and hover effects
- **Dynamic Navigation**: JavaScript-powered section navigation
- **Code Toggles**: Expandable code snippet sections
### Educational Content
- **Algorithm Explanations**: Detailed technical descriptions
- **Complexity Analysis**: Time and space complexity for each algorithm
- **Business Applications**: Real-world Amazon use cases
- **Performance Metrics**: Quantified efficiency improvements
- **Visual Diagrams**: Algorithm flow and data structure visualizations
### Academic Rigor
- **Research References**: Links to original algorithm papers
- **Academic Sources**: Peer-reviewed publications and documentation
- **Implementation Links**: GitHub repositories with source code
- **Citation Format**: Proper academic attribution
## š Getting Started
### Prerequisites
- Modern web browser (Chrome, Firefox, Safari, Edge)
- Local web server (optional, for development)
### Installation
1. **Clone the repository**
```bash
git clone https://github.com/yourusername/aps-portfolio.git
cd aps-portfolio
```
2. **Open in browser**
```bash
# Direct file access
open index.html
# Or serve locally (recommended)
python -m http.server 8000
# Then visit http://localhost:8000
```
3. **Navigate the portfolio**
- Start at `index.html` for the main portfolio
- Explore `business-cases.html` for detailed case studies
- Check `references.html` for academic sources
## š± Responsive Design
The portfolio is fully responsive with breakpoints at:
- **Mobile**: 320px - 768px
- **Tablet**: 768px - 1024px
- **Desktop**: 1024px+
## š Navigation Structure
```
Homepage (index.html)
āāā About Section
āāā Skills & Technologies
āāā Case Studies Preview
āāā Contact Information
Case Studies (business-cases.html)
āāā Algorithm Navigation Grid
āāā 19 Detailed Case Studies
āāā Interactive Code Snippets
āāā Performance Metrics
References (references.html)
āāā String Processing Papers
āāā Graph Algorithm Research
āāā Data Structure Documentation
āāā Amazon Technical Papers
āāā Implementation Code Links
```
## š Algorithm Complexity Overview
| Algorithm | Time Complexity | Space Complexity | Use Case |
|-----------|----------------|------------------|----------|
| Suffix Tree | O(n) | O(n) | Text Search |
| Dijkstra's | O((V + E) log V) | O(V) | Route Planning |
| PageRank | O(nĀ³) | O(nĀ²) | Trust Ranking |
| Hungarian | O(nĀ³) | O(nĀ²) | Assignment |
| A* Search | O(b^d) | O(b^d) | Pathfinding |
| LRU Cache | O(1) | O(capacity) | Caching |
## š Educational Value
This portfolio serves as:
- **Learning Resource**: Comprehensive algorithm explanations
- **Industry Application**: Real-world case studies
- **Interview Preparation**: Common technical interview topics
- **Academic Reference**: Properly cited research materials
- **Code Examples**: Practical implementation guidance
## š Academic Sources
The project references over 50 academic papers and publications including:
- Original algorithm papers (Dijkstra, 1959; Huffman, 1952)
- Amazon research publications
- Computer science textbooks (CLRS, Kleinberg & Tardos)
- University course materials (MIT, Stanford)
- Industry whitepapers and documentation
## š¤ Contributing
While this is a personal portfolio project, suggestions for improvements are welcome:
1. Fork the repository
2. Create a feature branch (`git checkout -b feature/improvement`)
3. Commit changes (`git commit -am 'Add improvement'`)
4. Push to branch (`git push origin feature/improvement`)
5. Create a Pull Request
## š License
This project is open source and available under the [MIT License](LICENSE).
## š¤ Author
**Pavan H Bhakta**
- Email: pavanbhakta16@gmail.com
- GitHub: [@bPavan16](https://github.com/bPavan16)
- LinkedIn: [Profile](https://linkedin.com/in/pavanbhakta-jul19)
## š Acknowledgments
- Amazon for inspiring these algorithmic applications
- Academic researchers whose papers made this analysis possible
- Open source community for tools and resources
- University professors and online educators
## š Future Enhancements
- [ ] Add more algorithm visualizations
- [ ] Include interactive algorithm simulators
- [ ] Expand to other tech companies (Google, Microsoft)
- [ ] Add performance benchmarking tools
- [ ] Create video explanations for complex algorithms
---
*This portfolio demonstrates the intersection of theoretical computer science and practical industry applications, showcasing how fundamental algorithms power modern technology at scale.*