Update pages/Life_cycle_of_ML.py

pages/Life_cycle_of_ML.py

@@ -2,27 +2,42 @@ import streamlit as st
 
 # HTML content inside a string for correct syntax
 html_content = """
-# Shapes in Markdown
+# Life Cycle of ML
 
-## Rectangle
+The life cycle of Machine Learning (ML) involves several stages, from defining the problem to deploying the model. Here's an overview of each stage:
+
+1. **Problem Definition:** Understanding the problem to define the goals and objectives of the ML model.
+2. **Data Collection:** Gathering relevant data required to train the model.
+3. **Data Preprocessing:** Cleaning and transforming the data into a usable format.
+4. **Model Building:** Building and training machine learning models using the processed data.
+5. **Evaluation:** Evaluating the performance of the model and adjusting it as needed.
+6. **Deployment:** Deploying the model into a production environment.
+
+---
+
+## Shapes Representing the ML Life Cycle
+
+### Rectangle: Problem Definition
 <div style="width: 200px; height: 100px; background-color: lightblue;"></div>
 
-## Circle
+### Circle: Data Collection
 <div style="width: 100px; height: 100px; border-radius: 50%; background-color: lightcoral;"></div>
 
-## Ellipse
+### Ellipse: Data Preprocessing
 <div style="width: 200px; height: 100px; border-radius: 50%; background-color: lightgreen;"></div>
 
-## SVG Shapes
+### SVG Shapes Representing ML Life Cycle
+
 <svg width="300" height="200">
-  <!-- Rectangle -->
+  <!-- Rectangle: Problem Definition -->
   <rect x="10" y="10" width="100" height="50" style="fill:lightblue;stroke:black;stroke-width:2" />
-  <!-- Circle -->
+  <!-- Circle: Data Collection -->
   <circle cx="200" cy="50" r="40" style="fill:lightcoral;stroke:black;stroke-width:2" />
-  <!-- Ellipse -->
+  <!-- Ellipse: Data Preprocessing -->
   <ellipse cx="200" cy="150" rx="85" ry="55" style="fill:lightgreen;stroke:black;stroke-width:2" />
 </svg>
 """
 
 # Render HTML content in Streamlit
 st.markdown(html_content, unsafe_allow_html=True)
+