This repository contains my personal notes and code examples related to Data Science. It is intended as a study companion and a knowledge base that I continuously update as I learn and explore new concepts.

• Python Basics

  • Variables, data types, functions, loops, conditionals

• NumPy & Pandas

  • Data manipulation, indexing, merging, reshaping

• Data Visualization

  • Using Matplotlib, Seaborn, and Plotly for visual insights

• Statistics & Probability

  • Descriptive stats, probability distributions, hypothesis testing

• Machine Learning

  • Supervised and unsupervised learning
  • Model building with Scikit-learn

• Model Evaluation

  • Metrics: Accuracy, Precision, Recall, F1 Score, ROC-AUC
  • Cross-validation techniques

• Mini Projects

  • Practice projects and Kaggle competition attempts

• Python 3.x
• Jupyter Notebook
• NumPy, Pandas, Scikit-learn
• Matplotlib, Seaborn, Plotly

📦data-science-notes
 ┣ 📂Anlasilir Ekonomi 
 ┣ ┣ 📂Python Ile Veri Analizi
 ┣ 📂HarvardX Machine Learning and Al with Python
 ┣ 📜README.md