Second workshop in our series on financial data automation and analysis. Outline covers Data Acquisition & Preprocessing (Yahoo Finance API, SQLite storage, generating additional variables); Exploratory Analysis & Time-Series Features; Forecasting Techniques (Prophet, ARIMA, Deep Learning); Visualization & Deployment (Plotly, Streamlit Cloud, GitHub Actions).

Join dotData Sr. Data Scientist Sharada Narayanan as she dives into the strengths, uses, and limitations of popular time-series forecasting techniques like ARIMA and Prophet.

Sharada will walk through real-world examples, share code snippets, and explore how ARIMA Prophet compare when building models using Feature Engineering techniques and advanced machine learning algorithms. Dive into the insights of each method and see how programmatic feature engineering and machine learning can supercharge your time series analysis.

Join dotData Sr. Data Scientist Sharada Narayanan as she dives into the strengths, uses, and limitations of popular time-series forecasting techniques like ARIMA and Prophet. Sharda will walk through real-world examples, share code snippets, and explore how ARIMA Prophet compare when building models using Feature Engineering techniques and advanced machine learning algorithms. Dive into the insights of each method and see how programmatic feature engineering and machine learning can supercharge your time series analysis.