Update pages/3_Life cycle of ML.py

pages/3_Life cycle of ML.py

@@ -11,15 +11,15 @@ def main():
 
     # Step descriptions and icons
     steps = [
-        {"title": "1. Problem Definition", "description": "Define the problem, goals, and success criteria.", "icon": "🔍"},
-        {"title": "2. Data Collection", "description": "Gather data from various sources.", "icon": "📊"},
-        {"title": "3. Data Cleaning", "description": "Handle missing values, remove duplicates, and fix errors.", "icon": "🧹"},
-        {"title": "4. Exploratory Data Analysis (EDA)", "description": "Understand data patterns and relationships.", "icon": "📈"},
-        {"title": "5. Feature Engineering", "description": "Create, transform, or select important features.", "icon": "🛠️"},
-        {"title": "6. Model Selection", "description": "Choose a suitable algorithm for the task.", "icon": "🤖"},
-        {"title": "7. Model Training", "description": "Train the model using the training dataset.", "icon": "🎯"},
-        {"title": "8. Model Evaluation", "description": "Assess the model's performance using metrics.", "icon": "📋"},
-        {"title": "9. Deployment", "description": "Deploy the model for real-world use.", "icon": "🌐"},
+        {"title": "1. Problem Definition", "description": "Objective of the project.", "icon": "🔍"},
+        {"title": "2. Data Collection", "description": "Data is collected from various sources like APIs, databases, or web scraping atlast we've to go with manual collection.", "icon": "📊"},
+        {"title": "3. Simple EDA", "description": "Describing the quality of the data.", "icon": "🧹"},
+        {"title": "4. Data Pre-processing", "description": "It is a technique by which we can convert raw data into pre-procesed data --->1.Clean the data  2.Transform the data.", "icon": "📈"},
+        {"title": "5. EDA", "description": "Transforming insights into a clean dataset and providing proper visualizations.", "icon": "🛠️"},
+        {"title": "6. Feature Engineering", "description": "Creating and analyzing features and labels.", "icon": "🤖"},
+        {"title": "7. Model Training", "description": "Training the machine about relationships between features and labels.", "icon": "🎯"},
+        {"title": "8. Model Testing", "description": "Testing how efficiently the machine learned.", "icon": "📋"},
+        {"title": "9. Deployment", "description": "Deploying the machine to the client and ensuring maintenance for accurate results", "icon": "🌐"},
         {"title": "10. Monitoring & Maintenance", "description": "Monitor the model and update as needed.", "icon": "📡"}
     ]
 
@@ -41,10 +41,5 @@ def main():
         with cols[idx]:
             st.markdown(f"{step['icon']} **{step['title']}**")
 
-    # Footer section with images or a final message
-    st.markdown("---")
-    st.markdown("**Tip:** The ML lifecycle is iterative; revisit steps as needed!")
-    st.image("https://upload.wikimedia.org/wikipedia/commons/thumb/3/3a/Machine_learning_lifecycle_diagram.jpg/1200px-Machine_learning_lifecycle_diagram.jpg", caption="Machine Learning Lifecycle", use_column_width=True)
-
 if __name__ == "__main__":
     main()