šŸ“ˆ Predicting Google Stock Prices with Kernel Regression and Interactive Widgets! šŸš€ | by Unicorn Day | Jul, 2024 – Nirantara – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra – Niraranra


Hey there, stock lovers! šŸ“Š Ever puzzled how one can predict stock prices using some fancy math? šŸ¤“ Successfully, proper now, weā€™re diving into the world of kernel regression with a contact of interactivity! šŸŽ‰ Letā€™s embark on this journey to predict Google stock prices using Python, statsmodels, and some cool widgetsā€¦ šŸŒŸ

šŸ§© Setting Up Our Devicesā€¦

First points first, we have now to gather our devices for this magical journey. šŸ› ļø Weā€™ll be using a combination of extremely efficient libraries like numpy, pandas, matplotlib, yfinance, statsmodels, and ipywidgets. That is the lineup:

# Arrange very important libraries
!pip arrange yfinance statsmodels matplotlib ipywidgets
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf
import statsmodels.api as sm
import ipywidgets as widgets
from ipywidgets import interactive

With these libraries, weā€™re in a position to fetch stock data, perform kernel regression, and make our visualization interactive! šŸŒˆ

šŸ’¾ Fetching Google Stock Informationā€¦

To start, weā€™d like some historic stock prices for Google (ticker picture: GOOGL). Our magic carry out fetch_data will simply do this. šŸŖ„

defā€¦

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If you havenā€™t already, we encourage you to download and experience these fantastic apps. Stay connected, informed, stylish, and explore amazing travel offers with the Nirantara family!

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Thank you for being a valued member of the Nirantara family! We appreciate your continued support and trust in our apps.

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