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Googles Stock Price Prediction
📈 Stock Price Prediction using Facebook Prophet
Forecasting | Time Series Analysis | Python
Overview
This project demonstrates how to predict Google’s stock prices using the Facebook Prophet model. It involves time series forecasting based on historical data obtained from Yahoo Finance, enabling accurate stock trend prediction for the next 365 days.
Objective
Utilize Facebook Prophet to forecast future stock prices and uncover seasonal trends using time series modeling techniques.
Tools & Libraries
Python – Pandas, NumPy, Matplotlib
Facebook Prophet – Time series forecasting
Jupyter Notebook – For data analysis and model building
Project Steps
Loaded historical Google stock data
Preprocessed data to meet Prophet’s input format
Trained the Prophet model on historical trends
Forecasted stock prices for 365 future days
Visualized both predictions and seasonal components
Output Highlights
📊 Line chart: Historical vs. Predicted Stock Prices
⏳ Seasonal Components: Trend, weekly, and yearly patterns
📅 Forecast graph for next 1 year of stock movement
Outcome
Successfully built a robust forecasting model using Prophet. This project illustrates my ability to work with real-world financial datasets, perform time series modeling, and extract business-relevant insights.





