I'm a data-driven explorer who blends statistical thinking with technical execution.
With a background in Full Stack Development and a growing expertise in Data Science, I craft solutions that make data meaningful, predictive, and actionable.
- 🧠 Passionate about Time Series Forecasting, GenAI, and Business Intelligence
- 📊 Strong command over EDA, Machine Learning, and Interactive Dashboards
- 💡 Exploring Vector Databases, Prompt Engineering, and LLMs to build smarter systems
- 🔍 Curious by nature — I love diving deep into complex datasets to uncover patterns and insights
| 🔣 Languages | 📊 Data & ML | 📈 Visualization | ⚙️ Tools & Platforms |
|---|---|---|---|
| Python, SQL, Bash | Pandas, NumPy, Scikit-learn, Statsmodels, XGBoost | Matplotlib, Seaborn, Plotly, Power BI | Jupyter, VSCode, Git, MySQL, PostgreSQL, Docker |
| TypeScript, JavaScript | Time Series (ARIMA, SARIMAX, LSTM), Deep Learning (TensorFlow/Keras) | Power BI, Excel Dashboards | Linux (Arch), Prompt Engineering, OpenAI APIs |
| -- | Vector DB (e.g. FAISS), LangChain (exploring) | Streamlit, Dash (basic) | -- |
- 📈 AAPL Stock Forecasting: Modeled 15 years of stock data using SARIMAX + exogenous inputs
- 🧠 Customer Churn Classifier: Used ML to predict churn with real-world datasets
- 🧾 Retail Dashboard: Visualized sales KPIs in Power BI with slicers and trends
- 🔁 EDA Automation Pipeline: Reusable module for preprocessing and visualization
- 🤖 Prompt Engineering Experiments: Testing GenAI use cases with real-world tasks
| 📂 Project | 📄 Description |
|---|---|
| AAPL Forecasting | Forecasted stock prices using SARIMAX with confidence intervals and interactive visuals. |
| Sales Dashboard | Built a business dashboard in Power BI using slicers, KPIs, and interactive charts. |
| ML Pipeline | Classification model + feature engineering to detect customer churn patterns. |
| EDA Notebook | Visual exploratory analysis using seaborn, plotly, and custom-built scripts. |
- 📧 Email: [email protected]
- 🌐 Portfolio
- 📝 Hashnode Blog
- ☕ Buy Me a Coffee
🧩 *Let’s build something data-driven, explainable, and impactful — together.*https://github.com/sadiqhasanrupani/stock-market-analysis