Welcome to my Data Science repository! 🚀
This repository is a collection of my studies, projects, and experiments in Data Science, covering various topics such as Machine Learning, Deep Learning, AutoML, and Data Analysis. The goal of this repository is to document my learning journey and share useful insights with others interested in the field.
The repository is organized into different sections, each containing Jupyter Notebooks with practical implementations of Data Science concepts. Some of the key topics covered include:
- FinalWorkPython.ipynb: A comprehensive project that demonstrates data preprocessing, exploratory data analysis (EDA), feature engineering, and predictive modeling.
- AutoML.ipynb: An introduction to Automated Machine Learning (AutoML), showcasing the use of libraries to optimize model selection and hyperparameter tuning.
- FinalProject_Updated.ipynb: A final project that integrates multiple Machine Learning techniques, feature selection methods, and model evaluation.
- Python (Pandas, NumPy, Matplotlib, Seaborn)
- Machine Learning (Scikit-learn, TensorFlow, PyTorch)
- AutoML (H2O, TPOT, Auto-sklearn)
- Data Visualization (Matplotlib, Seaborn, Plotly)
- Deep Learning (Keras, TensorFlow, PyTorch)
- SQL & NoSQL Databases
- Cloud Computing (AWS)
I will continue adding new projects covering topics such as:
- Advanced NLP with Transformers
- Deep Learning Architectures
- Time Series Forecasting
- Anomaly Detection
- Explainable AI (XAI)
If you find this repository helpful or have suggestions for improvements, feel free to open an issue or fork the repository. Let's collaborate and learn together!