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This beginner path introduces machine learning for financial analysis using Python, Pandas, and historical Tesla stock data. You will load, manipulate, and visualize financial time series while building a foundation in market data analysis.
You will construct technical indicators, including moving averages and exponential moving averages, and examine how they support market analysis. Next, you will prepare your data for machine learning through feature engineering, scaling, and time-aware train-test splitting.
Finally, you will train, tune, and evaluate a gradient boosting regression model to forecast stock price changes. The path is designed for learners beginning their study of financial data analysis and predictive modeling.
