This project showcases a comprehensive exploratory data analysis (EDA) of Tesla stock prices using various analytical tools, including Python, R, Power BI, and Microsoft Excel. The project involves examining historical Tesla stock data, performing EDA, and predicting stock prices for January 2024.

This repository hosts a stock market prediction model for Tesla and Apple using Liquid Neural Networks. It showcases data-driven forecasting techniques, feature engineering, and machine learning to enhance the accuracy of financial predictions.

Python script analyzes Tesla stock data, displaying candlestick chart, 3D scatter plot, & line chart (closing price, MA50, MA200). Generates buy/sell signals based on moving average crossovers.