This repository offers a wide range of Turkish resources and practical examples on artificial intelligence (AI), data science, machine learning (ML), and related technologies. It includes real-world inspired projects developed with Python and popular frameworks.
- To teach AI and data science topics through hands-on examples.
- To demonstrate the effective use of modern Python tools (Jupyter, FastAPI, Gradio, etc.).
- To provide practical knowledge on trending topics such as Large Language Models (LLMs), agent-based systems, and data generation.
- To create a continuously evolving knowledge base with an open-source philosophy.
| Folder/File | Description |
|---|---|
Daily Dose Codes/ |
Daily code snippets and programming tips |
Data-Codes/ |
Data generation, synthetic data creation, and data evaluation scripts |
Deep Learning/ |
TensorFlow/Keras image classifier project on CIFAR-10 dataset |
Fast API/ |
Modern web API application examples with FastAPI |
Fine Tuning/ |
Transfer learning and model fine-tuning examples |
Genel/ |
General-purpose Python scripts and utilities |
Google - Agents - Codes/ |
Agent applications integrated with Google services |
Gradio - MCP/ |
Interactive web apps with Gradio and MCP integration |
LLMS/ |
Applications with Large Language Models (LLMs) |
LM STUDIO/ |
Local LLM experiments with LM Studio |
Machine Learning/ |
Classical machine learning applications and data preprocessing techniques |
MCP/ |
Applications related to MCP |
MCP-Local/ |
Local development environment examples for MCP |
ML Practices/ |
Machine learning applications and model experiments |
MongoDB/ |
MongoDB usage examples and guides |
OCR/ |
Optical Character Recognition (OCR) applications and scripts |
Ollama Apps/ |
Local LLM applications built with the Ollama platform |
papers/ |
Academic papers, summaries, and analyses |
pdf_docs/ |
PDF documents and notes related to projects |
Python Learn/ |
Basic and intermediate Python exercises |
Qwen-Agent/ |
Qwen-based smart agent applications and Chrome extension |
RAG/ |
Retrieval-Augmented Generation (RAG) applications and examples |
Scrape/ |
Web scraping, data extraction, and automation scripts |
.gitignore |
Git ignore configuration |
huggingface-kernel-hub.py |
Example Python script for Hugging Face kernel hub |
LICENSE |
License (Apache 2.0) |
mongodb-mcp-server.md |
MongoDB MCP server & Cursor IDE integration guide |
README.md |
Main project description (this file) |
requirements.txt |
General Python dependencies list |
Classification/ |
YouTube yorumlarında spam tespiti (TF-IDF + MultinomialNB + GridSearchCV) |
Projects are generally developed with Python 3.8+.
To install general dependencies:
pip install -r requirements.txtSome subfolders may have their own dependencies; check their README.md or requirements.txt files for details.
- Bug Reports: Submit via GitHub Issues.
- Feature Requests: Use Issues for new ideas.
- Pull Requests: Feel free to contribute code or documentation!
This repository and its content are licensed under Apache License 2.0.