Project Overview

This project focuses on analyzing Tech-based companies' stock prices using machine learning models. The dataset used in this project is titled "World-Stock-Prices-Dataset". The code provided includes data preprocessing, exploratory data analysis (EDA), model training, evaluation, and prediction.

Getting Started

To run the project, please follow these instructions:

1. Download the zip file to your local machine.
2. Ensure that both the submitted code and the dataset file "World-Stock-Prices-Dataset.csv" are placed in the same folder.
3. Make sure your Python environment has all the required libraries installed.

Installation

Before running the project, ensure that your system has the following libraries installed. You can install them using pip, the Python package manager:

pip install tensorflow
pip install scikit-learn
pip install pandas
pip install matplotlib

Running the Project

Once all the necessary libraries are installed, you can run the project successfully. Execute the provided code in your preferred Python environment.

Additional Notes

• The provided code includes data preprocessing, exploratory data analysis, model training, evaluation, and prediction steps.
• For any inquiries or issues regarding the project, please feel free to contact the project owner.

Contributors

• Purva Patel