Update pages/Machine Learning vs Deep Learning.py

pages/Machine Learning vs Deep Learning.py

@@ -1,43 +0,0 @@
-import streamlit as st
-import pandas as pd
-
-# Define the table data
-data = {
-    "Aspect": [
-        "Learning Approach", "Data Requirement", "Complexity of Tasks",
-        "Computation Power", "Algorithms Used", "Training Time", "Data Types Processed"
-    ],
-    "Machine Learning (ML)": [
-        "Uses a statistical approach to analyze data and make predictions.",
-        "Works well with smaller datasets.",
-        "Handles simpler relationships (e.g., predicting house prices).",
-        "Can run on CPUs (low computational power).",
-        "Uses models like KNN, Decision Trees, Linear Regression.",
-        "Faster training due to simpler computations.",
-        "Works with structured/tabular data."
-    ],
-    "Deep Learning (DL)": [
-        "Uses neural networks to automatically learn patterns.",
-        "Requires large amounts of data to perform well.",
-        "Handles complex relationships (e.g., object recognition in images).",
-        "Requires GPUs/TPUs (high computational power).",
-        "Uses ANN, CNN, RNN for feature extraction and learning.",
-        "Longer training time due to deep layers and complex processing.",
-        "Works with images, videos, text, and audio."
-    ]
-}
-
-# Create DataFrame
-df = pd.DataFrame(data)
-
-# Display the table in Streamlit
-st.title("Machine Learning vs. Deep Learning")
-st.write("### Comparison Table")
-st.table(df)
-
-# Convert DataFrame to HTML
-html_table = df.to_html(index=False, escape=False)
-
-# Display HTML table
-st.write("### HTML Representation")
-st.code(html_table, language="html")