To build a machine learning model that can predict stock market trends based on educational factors.
To analyze the impact of educational trends on stock market performance.
To utilize Python programming language for data preprocessing, feature selection, model training, and prediction.
Collect and preprocess relevant data sets related to education and stock market performance.
Select appropriate machine learning algorithms for stock market prediction based on educational factors.
Train and optimize the machine learning model using Python libraries such as scikit-learn and tensorflow.
Evaluate the model performance using metrics such as accuracy, precision, recall, and F1 score.
Interpret the results and draw conclusions on the influence of education on stock market prediction.
