Update pages/4.Life Cycle of ML.py
Browse files- pages/4.Life Cycle of ML.py +21 -30
pages/4.Life Cycle of ML.py
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@@ -1,36 +1,29 @@
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import streamlit as st
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import os
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# Sidebar for navigation
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st.sidebar.title("Navigation")
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pages = st.sidebar.radio(
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if pages == "Life Cycle of ML":
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st.title("Life Cycle of Machine Learning")
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st.write("Explore the steps involved in the Machine Learning lifecycle.")
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if st.button("Problem Satement"):
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st.experimental_set_query_params(pages="Problem_Satement")
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if st.button("Data Collection"):
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st.experimental_set_query_params(pages="data_collection")
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if st.button("Simple EDA"):
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st.experimental_set_query_params(pages="Simple_EDA")
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if st.button("Data Pre-processing"):
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st.experimental_set_query_params(pages="Data_Pre-processing")
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if st.button("Exploratory Data Analysis (EDA)"):
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st.experimental_set_query_params(pages="Exploratory_Data_Analysis_(EDA)")
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if st.button("Feature Engineering"):
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st.experimental_set_query_params(pages="Feature_Engineering")
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if st.button("Training"):
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st.experimental_set_query_params(pages="Training")
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if st.button("Testing"):
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st.experimental_set_query_params(pages="Testing")
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if st.button("Deployment"):
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st.experimental_set_query_params(pages="Deployment")
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if st.button("Monitoring"):
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st.experimental_set_query_params(pages="Monitoring")
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elif pages == "Data Collection":
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st.title("Data Collection")
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@@ -42,10 +35,8 @@ elif pages == "Data Collection":
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st.write("### Structured Data Formats:")
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format_selected = st.radio("Choose a data format:", ["Excel", "CSV", "SQL Database"])
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if format_selected == "Excel":
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st.experimental_set_query_params(
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# Handling query parameters for structured data navigation
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query_params = st.experimental_get_query_params()
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if query_params.get("pages", [None])[0] == "structured_excel":
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st.title("Excel Data Format")
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st.write("#### What is Excel?")
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@@ -75,15 +66,15 @@ if query_params.get("pages", [None])[0] == "structured_excel":
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- Convert to a supported format if needed.
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""")
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# Button to download a Jupyter Notebook or PDF
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st.markdown("### Download Coding Guide:")
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file_path = "Excel_guide.ipynb" # Ensure this file exists in the app directory
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with open(file_path, "rb") as file:
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st.download_button(
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label="Download Excel Guide",
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data=file,
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file_name="Excel_guide.ipynb",
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mime="application/octet-stream",
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)
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import streamlit as st
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import os
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# Sidebar for navigation
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st.sidebar.title("Navigation")
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pages = st.sidebar.radio(
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"Go to:",
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["Life Cycle of ML", "Problem Statement", "Data Collection",
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"Simple EDA", "Data Pre-processing", "Exploratory Data Analysis (EDA)",
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"Feature Engineering", "Training", "Testing", "Deployment", "Monitoring"]
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)
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# Main Navigation Logic
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query_params = st.experimental_get_query_params()
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if pages == "Life Cycle of ML":
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st.title("Life Cycle of Machine Learning")
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st.write("Explore the steps involved in the Machine Learning lifecycle.")
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for button_name in [
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"Problem Statement", "Data Collection", "Simple EDA",
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"Data Pre-processing", "Exploratory Data Analysis (EDA)",
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"Feature Engineering", "Training", "Testing", "Deployment", "Monitoring"
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]:
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if st.button(button_name):
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st.experimental_set_query_params(pages=button_name.replace(" ", "_"))
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elif pages == "Data Collection":
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st.title("Data Collection")
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st.write("### Structured Data Formats:")
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format_selected = st.radio("Choose a data format:", ["Excel", "CSV", "SQL Database"])
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if format_selected == "Excel":
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st.experimental_set_query_params(pages="structured_excel")
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if query_params.get("pages", [None])[0] == "structured_excel":
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st.title("Excel Data Format")
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st.write("#### What is Excel?")
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- Convert to a supported format if needed.
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""")
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st.markdown("### Download Coding Guide:")
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file_path = "Excel_guide.ipynb"
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if os.path.exists(file_path):
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with open(file_path, "rb") as file:
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st.download_button(
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label="Download Excel Guide",
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data=file,
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file_name="Excel_guide.ipynb",
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mime="application/octet-stream",
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)
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else:
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st.error("The file 'Excel_guide.ipynb' does not exist. Please add it to the application directory.")
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