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Update pages/Life_cycle_of_ML.py
Browse files- pages/Life_cycle_of_ML.py +52 -66
pages/Life_cycle_of_ML.py
CHANGED
@@ -5,118 +5,104 @@ def display_lifecycle_stage(stage_name, description):
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st.subheader(stage_name)
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st.write(description)
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#
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st.title("Machine Learning Life Cycle")
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# Markdown Diagram
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st.markdown(
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"""
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+-----------------------+
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| Testing |
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+-----------------------+
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v
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+-----------------------+
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| Deployment |
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+-----------------------+
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v
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+-----------------------+
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| Monitoring |
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+-----------------------+
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```
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"""
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# Buttons for each stage
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col1, col2 = st.columns(2)
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with col1:
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if st.button("Problem Statement"):
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display_lifecycle_stage(
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"Problem Statement",
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"Defining the problem and setting objectives for the machine learning project."
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)
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if st.button("Simple EDA"):
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display_lifecycle_stage(
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"Simple EDA",
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"Performing initial exploratory data analysis to understand data distribution and trends."
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)
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if st.button("EDA"):
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display_lifecycle_stage(
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"EDA",
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"Detailed exploratory data analysis for deeper insights into data patterns."
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)
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if st.button("Training"):
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display_lifecycle_stage(
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"Training",
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"Fitting the model using the training dataset to learn patterns and relationships."
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)
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if st.button("
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display_lifecycle_stage(
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"
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"Deploying the trained model to production for real-world use."
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)
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with col2:
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if st.button("Data Collection"):
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display_lifecycle_stage(
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"Data Collection",
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"Gathering the data required for the machine learning project."
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)
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if st.button("Data Preprocessing"):
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display_lifecycle_stage(
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"Data Preprocessing",
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"Cleaning and transforming the data to prepare it for analysis."
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)
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if st.button("Feature Engineering"):
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display_lifecycle_stage(
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"Feature Engineering",
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"Creating new features or modifying existing ones to improve model performance."
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)
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if st.button("Testing"):
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display_lifecycle_stage(
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"Testing",
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"Evaluating the model's performance using a separate testing dataset."
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)
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if st.button("Monitoring"):
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display_lifecycle_stage(
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"Monitoring",
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"Monitoring the deployed model's performance and maintaining its accuracy."
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)
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st.subheader(stage_name)
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st.write(description)
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# Title
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st.title("Enhanced Machine Learning Life Cycle")
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# Markdown Diagram with Shapes and Colors
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st.markdown(
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"""
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<style>
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.shape-box {
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background-color: #FFDDC1;
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padding: 10px;
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border-radius: 5px;
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text-align: center;
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margin-bottom: 10px;
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}
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.shape-circle {
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background-color: #C1E1FF;
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padding: 10px;
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border-radius: 50%;
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text-align: center;
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margin-bottom: 10px;
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}
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.shape-diamond {
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background-color: #C1FFC1;
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padding: 10px;
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clip-path: polygon(50% 0%, 100% 50%, 50% 100%, 0% 50%);
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text-align: center;
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margin-bottom: 10px;
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}
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</style>
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<div class="shape-box">Problem Statement</div>
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<div class="shape-circle">Data Collection</div>
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<div class="shape-box">Simple EDA</div>
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<div class="shape-diamond">Data Preprocessing</div>
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<div class="shape-box">EDA</div>
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<div class="shape-circle">Feature Engineering</div>
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<div class="shape-box">Training</div>
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<div class="shape-diamond">Testing</div>
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<div class="shape-box">Deploying</div>
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<div class="shape-circle">Monitoring</div>
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""",
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unsafe_allow_html=True,
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)
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# Buttons for each stage
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st.markdown("### Select a Lifecycle Stage to Learn More:")
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col1, col2 = st.columns(2)
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with col1:
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if st.button("Problem Statement"):
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display_lifecycle_stage(
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"Problem Statement",
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"Defining the problem and setting objectives for the machine learning project."
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)
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if st.button("Simple EDA"):
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display_lifecycle_stage(
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"Simple EDA",
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"Performing initial exploratory data analysis to understand data distribution and trends."
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)
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if st.button("EDA"):
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display_lifecycle_stage(
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"EDA",
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"Detailed exploratory data analysis for deeper insights into data patterns."
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)
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if st.button("Training"):
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display_lifecycle_stage(
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"Training",
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"Fitting the model using the training dataset to learn patterns and relationships."
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)
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if st.button("Deploying"):
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display_lifecycle_stage(
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"Deploying",
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"Deploying the trained model to production for real-world use."
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)
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with col2:
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if st.button("Data Collection"):
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display_lifecycle_stage(
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"Data Collection",
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"Gathering the data required for the machine learning project."
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)
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if st.button("Data Preprocessing"):
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display_lifecycle_stage(
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"Data Preprocessing",
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"Cleaning and transforming the data to prepare it for analysis."
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)
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if st.button("Feature Engineering"):
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display_lifecycle_stage(
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"Feature Engineering",
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"Creating new features or modifying existing ones to improve model performance."
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)
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if st.button("Testing"):
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display_lifecycle_stage(
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"Testing",
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"Evaluating the model's performance using a separate testing dataset."
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)
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if st.button("Monitoring"):
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display_lifecycle_stage(
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"Monitoring",
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"Monitoring the deployed model's performance and maintaining its accuracy."
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)
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