Update pages/2.Introduction to Data Science.py

pages/2.Introduction to Data Science.py

@@ -2,39 +2,7 @@ import streamlit as st
 import numpy as np 
 import pandas as pd 
 
-st.header("**Data Science**")
-st.subheader(":red[**What do you mean by Data Science**]")
-st.write("Data Science is all about using data to find patterns, make predictions, and solve problems. It combines knowledge from fields like statistics, programming, and domain expertise to turn raw data into meaningful insights.Data Science helps us make better decisions using data.")
-st.subheader(":red[**Examples of Data Science**]")
-st.write("""
-**1.Netflix or YouTube Recommendations**
--Netflix uses data science to recommend shows based on what you’ve watched before.
-**2.Weather Forecasting**
--Predicting rain or sunny days based on historical weather data.
-**3.Fraud Detection in Banks**
--Detecting unusual spending patterns to prevent credit card fraud.
-**4.Sports Analytics**
--Analyzing players' performances to make better team strategies.
-**5.Healthcare**
--Predicting diseases based on patient symptoms or past data.
-""")
 
 
-st.subheader(":red[**What do you mean by Artificial Intelligence**]")
-st.write("""Artificial Intelligence (AI) is a way of teaching computers to think and act like humans.
-It means making machines smart enough to:
-- Solve problems
-- Make decisions
-- Learn from experience
-""")
-st.write("AI is like giving a computer a brain but it’s not as powerful as the human brain. It follows rules and learns from data.")
-st.subheader(":red[**Examples of AI in Everyday Life**]")
-st.write("""
-- Siri, Alexa, or Google Assistant uses AI to understand your voice and respond.
-- YouTube or Netflix suggests videos based on what you like.
-- AI shows you products based on your previous searches and purchases.
-- AI-powered chat systems answer customer questions on websites.
-""")
-