Skip to content

README.md

Latest commit

 

History

History
72 lines (55 loc) · 1.93 KB

README.md

File metadata and controls

72 lines (55 loc) · 1.93 KB

Yapay Zeka - 583839

This repository contains machine learning projects developed for the Artificial Intelligence course (583839).

Project 1: Machine Learning (Proje1_MakineOgrenmesi)

A comprehensive machine learning project covering classification, clustering, regression, and deep learning.

Project Structure

Proje1_MakineOgrenmesi/
│
├── 1_Siniflandirma/
│   └── Proje1_Bolum1_Siniflandirma.ipynb
│
├── 2_Kumeleme_Regresyon/
│   └── Proje1_Bolum2_Kumeleme_Regresyon.ipynb
│
├── 3_DerinOgrenme/
│   ├── Proje1_Bolum3_DerinOgrenme.ipynb
│   └── proje_veri_seti/
│       ├── bardak/
│       ├── kalem/
│       └── klavye/
│
└── Proje1_Raporu/

Part 1: Classification

  • Exploratory Data Analysis (EDA)
  • Multiple classification algorithms (Random Forest, SVM, Naive Bayes, K-NN)
  • Model comparison and evaluation
  • Performance metrics and visualization

Part 2: Clustering and Regression

  • Clustering Analysis:

    • K-Means, Agglomerative Clustering, DBSCAN
    • Elbow Method for optimal cluster selection
    • Silhouette Score and Adjusted Rand Index evaluation

  • Regression Analysis:

    • Linear Regression, Ridge, Lasso
    • Random Forest Regressor, SVR
    • MSE, RMSE, MAE, R² metrics

Part 3: Deep Learning

  • Image classification with Convolutional Neural Networks (CNN)
  • Transfer Learning with VGG16
  • Data Augmentation techniques
  • Model training, evaluation, and deployment

Requirements

pip install pandas numpy matplotlib seaborn scikit-learn tensorflow keras pillow opencv-python

Usage

  1. Clone the repository
  2. Install required packages
  3. Open Jupyter Notebook files
  4. Follow the instructions in each notebook

Author

Developed as part of the Artificial Intelligence course - 583839

License

This project is for educational purposes.