sree4411 commited on
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c1b0436
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Update pages/3_Life Cycle Of ML Project.py

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  1. pages/3_Life Cycle Of ML Project.py +23 -23
pages/3_Life Cycle Of ML Project.py CHANGED
@@ -8,22 +8,22 @@ def display_content(stage):
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  st.markdown("### Problem Statement\nIdentify the problem you want to solve and set clear objectives and success criteria.")
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  elif stage == "Data Collection":
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  st.markdown("### Data Collection\nGather relevant data from various sources and store it in a structured format.")
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- elif stage == "Data Preparation":
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- st.markdown("### Data Preparation\nClean, transform, and engineer features from the data to prepare it for modeling.")
 
 
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  elif stage == "Exploratory Data Analysis (EDA)":
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  st.markdown("### Exploratory Data Analysis (EDA)\nVisualize and analyze the data to understand its distributions and relationships.")
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- elif stage == "Model Selection":
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- st.markdown("### Model Selection\nChoose appropriate machine learning algorithms and develop a baseline model.")
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  elif stage == "Model Training":
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  st.markdown("### Model Training\nTrain the model using the training data and optimize its parameters.")
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- elif stage == "Model Evaluation":
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- st.markdown("### Model Evaluation\nAssess the model's performance using various metrics and cross-validation techniques.")
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  elif stage == "Model Deployment":
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  st.markdown("### Model Deployment\nIntegrate the trained model into a production environment and monitor its performance.")
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- elif stage == "Model Maintenance":
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- st.markdown("### Model Maintenance\nPeriodically retrain the model with new data and update features as needed.")
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- elif stage == "Documentation and Reporting":
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- st.markdown("### Documentation and Reporting\nDocument the entire project and share the results and insights with stakeholders.")
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  # Title and Introduction
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  st.title(":red[Lifecycle of a Machine Learning Project]")
@@ -38,19 +38,19 @@ if st.button(":blue[🌟 Problem Statement]"):
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  display_content("Problem Statement")
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  if st.button(":blue[πŸ“Š Data Collection]"):
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  display_content("Data Collection")
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- if st.button(":blue[πŸ› οΈ Data Preparation]"):
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- display_content("Data Preparation")
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- if st.button(":blue[πŸ” Exploratory Data Analysis (EDA)]"):
 
 
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  display_content("Exploratory Data Analysis (EDA)")
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- if st.button(":blue[πŸ€– Model Selection]"):
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- display_content("Model Selection")
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- if st.button(":blue[πŸ‹οΈ Model Training]"):
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  display_content("Model Training")
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- if st.button(":blue[πŸ“ˆ Model Evaluation]"):
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- display_content("Model Evaluation")
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- if st.button(":blue[πŸš€ Model Deployment]"):
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  display_content("Model Deployment")
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- if st.button(":blue[πŸ”§ Model Maintenance]"):
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- display_content("Model Maintenance")
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- if st.button(":blue[πŸ“ Documentation and Reporting]"):
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- display_content("Documentation and Reporting")
 
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  st.markdown("### Problem Statement\nIdentify the problem you want to solve and set clear objectives and success criteria.")
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  elif stage == "Data Collection":
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  st.markdown("### Data Collection\nGather relevant data from various sources and store it in a structured format.")
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+ elif stage == "Simple EDA":
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+ st.markdown("### Simple EDA\nPerform exploratory data analysis to understand data distributions and relationships..")
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+ elif stage == "Data Pre-Processing":
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+ st.markdown("### Data Pre-Processing\nhere we convert raw data into cleaned data, it involves two steps Cleaning and Transforming.")
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  elif stage == "Exploratory Data Analysis (EDA)":
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  st.markdown("### Exploratory Data Analysis (EDA)\nVisualize and analyze the data to understand its distributions and relationships.")
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+ elif stage == "Feature Engineering":
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+ st.markdown("### Feature Engineering\nHere we can create our own new features.")
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  elif stage == "Model Training":
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  st.markdown("### Model Training\nTrain the model using the training data and optimize its parameters.")
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+ elif stage == "Model Testing":
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+ st.markdown("### Model Testing\nAssess the model's performance using various metrics and cross-validation techniques.")
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  elif stage == "Model Deployment":
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  st.markdown("### Model Deployment\nIntegrate the trained model into a production environment and monitor its performance.")
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+ elif stage == "Monitoring":
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+ st.markdown("### Monitoring\nPeriodically retrain the model with new data and update features as needed.")
 
 
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  # Title and Introduction
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  st.title(":red[Lifecycle of a Machine Learning Project]")
 
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  display_content("Problem Statement")
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  if st.button(":blue[πŸ“Š Data Collection]"):
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  display_content("Data Collection")
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+ if st.button(":blue[πŸ› οΈ Simple EDA]"):
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+ display_content("Simple EDA")
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+ if st.button(":blue[πŸ” Data Pre-Processing"):
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+ display_content("Data Pre-Processing")
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+ if st.button(":blue[πŸ“ˆExploratory Data Analysis (EDA)]"):
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  display_content("Exploratory Data Analysis (EDA)")
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+ if st.button(":blue[πŸ‹οΈ Feature Engineering]"):
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+ display_content("Feature Engineering")
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+ if st.button(":blue[Model Training]"):
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  display_content("Model Training")
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+ if st.button(":blue[πŸ”§Model Testing]"):
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+ display_content("Model Testing")
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+ if st.button(":blue[πŸš€Model Deployment]"):
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  display_content("Model Deployment")
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+ if st.button(":blue[πŸ“ Monitoring]"):
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+ display_content("Monitoring")