Portfolio

Articles in Medium.com by Tim Ozdemir

1. Community Health Workers (CHW) Hypertension Mentor submitted for Kaggle Google DeepMind - Vibe Code with Gemini 3 Pro in AI Studio (2025) (Google AI Studio, Vibe Coding, Prompt Engineering)
   1. 
   2. Video
   3. HeartGuard Chatbot
2. AI Farming Buddy in Lesotho capstone project for 5-Day AI Agents Intensive Course with Google (2025) (Google ADK, Multi-Agent, MCP Servers, Tools, LLM Agents, Workflow: Coordinator, Weather, Farming, External API, DuckDB)
   1. , use link Capstone Architecture Diagram
   2. Kaggle Notebook
   3. Writeup on AI Farming Buddy in Lesotho
3. GenAI-Driven SDLC : Generate React UI Code (2025)
4. GenAI-Driven SDLC (2025)
5. System Design: Food Delivery System (2025)
6. Algorithm Interview by Example: Process (2020)
7. Algorithm Interview by Example: Random Selection (2020)

Drafts

1. System Design: Food Delivery System, Proximity Search (2025)
   • Location Update to Redis (Redis, multi-thread motion simulation of delivery agents, Python)
   • NNQ: Uber H3 Spatial Index Jupyter Notebook (Uber H3, Folium, Python)
   • NNQ: R-Tree vs H3 Index Jupyter Notebook (DuckDB, R-Tree, Uber H3, Pandas, Folium, Python, SQL,…)
   • Note: Distance calculation between spatial points (locations) (DuckDB,PostGIS, SQL, Python)
   • Note: ElasticSearch for Nearest Neighbour Query / Proximity Search (Elasticsearch, NNQ, Python)
   • Note: Redis for Proximity Search (Redis, Lua Scripting, NNQ, Python)
   • Note: PostgreSQL and PostGIS for Nearest Neighbour Query / Proximity Search (Postgresql, PostGIS, psycopg2, NNQ, Python)
2. Chat with your book (LLM with RAG) (streamlit, LangChain, OpenAI) (2025)
   • Calculate The Number Of Tokens (tiktoken)
   • Vector stores with FAISS, indexing and search visualization (FAISS, Dimension reduction(t-SNE, PCA), 2D/3D Visualization (Matplotlib, Plotly), LangChain, Hugging Face, Local LLM)
   • Note: Elasticsearch for Semantic Search (Elasticsearch, DSL, Semantic search, dense vectors, Text Embedding, Sentence-Transformers, Hugging Face (all-MiniLM-L6-v2,embeddinggemma-300m), Seaborn, Python)
3. Open API: Adding summary of context history (Prompts for role: user and assistant) (2025)
4. Open API: Classification (utilize prompts of user-assitant for sample-label) (2025)
5. Open API: F(dietary restrictions, cuisine, available ingirendients) => Recipe (2025)
6. Open API: Recipes enhanced with Model Context Protocol (MCP) to pull in external trusted data (2025)
7. Java Streaming API Example (2025)
   • Spring Boot sample application (Java 23, Maven, H2 Database, Spring Boot, JUnit 5, ) (2025)
   • Concurrency:Executors and ExecutorService
8. Algorithm Interview by Example: Reduction (2025)
9. Prompt Engineering practices with Claude (2025)
   • Conversation with Claude Samples Jupyter Notebook (Claude API, Prompt: Context, System Prompt, Temperature; Python)
   • Prompt Optimization