I'm a Machine Learning & Deep Learning enthusiast passionate about building intelligent systems and exploring the world of AI.
Currently focusing on Artificial Neural Networks (ANNs)
- 🎓 Self-taught learner passionate about AI, ML, and DL
- 🚀 Building predictive models and data visualizations using Python and modern ML libraries
- 🌱 Currently learning advanced neural network architectures and model optimization techniques
- 🎯 On the path to becoming an AI & ML Engineer, with a strong focus on Deep Learning
| Project Title | Description | Tech Stack | GitHub Link |
|---|---|---|---|
| Student Performance Prediction (DL) | End-to-end deep learning pipeline for analyzing student academic performance. Includes EDA, preprocessing, regression, classification, and evaluation. | Python, Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, Keras, Scikit-learn | View Repo |
| Hotel Review Analysis & Prediction | Predicts hotel review scores using structured metadata. Includes regression models, visual diagnostics, and reproducible workflow. | Python, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, XGBoost | View Repo |
| Lung Cancer Prediction (ML) | Predicts cancer likelihood using ML classifiers. Includes preprocessing, model training, and evaluation. | Python, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn | View Repo |
| Auto Price Prediction (XGBoost) | Regression model for estimating car prices using XGBoost. Includes feature engineering and model tuning. | Python, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, XGBoost | View Repo |
| Airline Insights ML Analysis | EDA and forecasting on airline operations data. Includes time series analysis and visual storytelling. | Python, Pandas, NumPy, Matplotlib, Seaborn, Statsmodels, Scikit-learn | View Repo |
📧 arianjafar59@gmail.com
💡 I’m always open to collaborations, learning opportunities, and discussions about AI, ML, and DL.
⭐ “Code. Learn. Iterate. Intelligence is built, one model at a time.”