Exploratory data analysis and predictive modeling for Kaggle's monthly tabular data challenges, testing various machine learning approaches on structured datasets.
Advanced regression techniques applied to predict home values using 79 housing features, with feature engineering and hyperparameter optimization.
Computer vision model to classify handwritten characters using convolutional neural networks (CNNs) and image preprocessing techniques.
Career path analysis examining factors influencing post-graduate education choices using statistical methods and visualization.
Behavioral analytics exploring smartphone usage patterns through EDA and time series analysis of app engagement data.
Music industry analytics investigating streaming trends, genre popularity, and temporal patterns in listening habits.
Educational data mining assessing academic outcomes based on demographic and socioeconomic factors.
Predictive Modeling: Regression, classification, time series forecasting
Data Storytelling: Clear visualizations and actionable insights
End-to-End ML: From data cleaning to model deployment
Cross-Domain Applications: Education, music, real estate, and more
▸ Data Analysis: Pandas | NumPy | SciPy
▸ Visualization: Matplotlib | Seaborn | Plotly
▸ Machine Learning: Scikit-learn | XGBoost | LightGBM
▸ Deep Learning: TensorFlow/Keras (for CV projects)
▸ NLP: spaCy | NLTK (for text-based projects)