Predict Stock Prices with Python Using Live Data | Step-by-Step Tutorial (AAPL, TSLA, MSFT)
Learn how to predict stock prices using Python, Jupyter Notebook, and live data from Yahoo Finance. In this beginner-friendly tutorial, we walk through downloading stock data (AAPL, TSLA, MSFT), cleaning it, building a linear regression model, and visualizing predictions with interactive charts using Plotly.
Perfect for beginners in Python, data science, and analytics!
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LIST OF TICKERS : You can replace the ticker in the video to view any of these company stocks for prediction.
Tech Stocks
Apple -- AAPL
Microsoft -- MSFT
Google ( Alphabet) GOOGL
Amazon -- AMZN
Meta (Facebook) META
Tesla -- TSLA
Netflix -- NFLX
Financial
JPMorgan Chase -- JPM
Bank of America -- BAC
Wells Fargo -- WFC
Goldman Sachs -- GS
Consumer Brands
Walmart -- WMT
Coca-Cola -- KO
PepsiCo -- PEP
Nike -- NKE
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If you’re learning Python for data analytics and want a structured guide, I put everything into a book with real examples.
📘 Python for Data Cleaning → 👉 https://a.co/d/iiMzQQH
Thank you for watching.
#Python #StockPrediction #JupyterNotebook #DataScience #AAPL #TSLA #MSFT #MachineLearning #Plotly
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