📈 Predicting Google Stock Prices with Kernel Regression and Interactive Widgets! 🚀 | by Unicorn Day | Jul, 2024 – Niraranra

Hey there, inventory lovers! 📊 Ever puzzled how one can predict inventory costs utilizing some fancy math? 🤓 Efficiently, correct now, we’re diving into the world of kernel regression with a contact of interactivity! 🎉 Let’s embark on this journey to foretell Google inventory costs utilizing Python, statsmodels, and a few cool widgets… 🌟

🧩 Setting Up Our Units…

First factors first, we’ve acquired to assemble our units for this magical journey. 🛠️ We’ll be utilizing a mixture of extraordinarily environment friendly libraries like numpy, pandas, matplotlib, yfinance, statsmodels, and ipywidgets. That’s the lineup:

# Organize essential libraries
!pip organize 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, we’re able to fetch inventory data, carry out kernel regression, and make our visualization interactive! 🌈

💾 Fetching Google Inventory Knowledge…

To start out, we’d like some historic inventory costs for Google (ticker image: GOOGL). Our magic perform fetch_data will merely do this. 🪄

def…

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