Update pages/2.Introduction to Data Science.py

pages/2.Introduction to Data Science.py

@@ -8,14 +8,19 @@ st.write("Data Science is all about using data to find patterns, make prediction
 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.
 """)
 
@@ -87,10 +92,10 @@ st.write("""**Examples:** 1.Imagine you want a computer to recognize handwritten
 - Input Data: Provide many images of handwritten numbers with labels (e.g., “This is 5”).
 - Training: A neural network learns the patterns in these images, like the curves of "5."
 - Prediction: When you show it a new handwritten digit, it predicts what number it is.
-2.Understand and respond to your voice using deep learning.
-3.Unlocking your phone by recognizing your face.
-4.Identifying diseases from X-rays or MRI scans.
-5.Suggesting what to watch next based on your viewing history.
+- 2.Understand and respond to your voice using deep learning.
+- 3.Unlocking your phone by recognizing your face.
+- 4.Identifying diseases from X-rays or MRI scans.
+- 5.Suggesting what to watch next based on your viewing history.
 """)
 
 st.subheader(":red[**Types of Neural Networks in Deep Learning**]")