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Update app.py

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  1. app.py +3 -3
app.py CHANGED
@@ -35,14 +35,14 @@ def home_page():
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  st.image("https://i.ytimg.com/vi/WULwst0vW8g/maxresdefault.jpg")
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  st.write("""
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- The Income Prediction Challenge for Azubian is a machine learning project that aims to predict whether an individual's income falls above or below a specific income threshold. This information can be used to monitor income inequality and inform policy decisions.
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  """)
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  # The Problem of Income Inequality
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  st.header("The Problem: Income Inequality πŸ’Έ")
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  st.write(
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  """
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- Income inequality, a pervasive challenge that hinders economic progress and social well-being, demands innovative solutions. The "Income Prediction Challenge for Azubian" tackles this issue head-on, harnessing the power of machine learning to predict individual income levels.
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  **Key Challenges of Income Inequality:** ⚠
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@@ -81,7 +81,7 @@ def solution():
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  st.header("Solution πŸ’‘: Combating Income Inequality with Data-Driven Solutions πŸ“ˆ ")
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  st.write("""
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- The "Income Prediction Challenge for Azubian" utilizes machine learning to predict individual income levels, providing valuable data to policymakers for informed action. This data-driven approach offers several advantages:
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  * **Cost-Effectiveness:** πŸ’°
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  st.image("https://i.ytimg.com/vi/WULwst0vW8g/maxresdefault.jpg")
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  st.write("""
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+ This application is a machine learning project that aims to predict whether an individual's income falls above or below a specific income threshold. This information can be used to monitor income inequality and inform policy decisions.
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  """)
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  # The Problem of Income Inequality
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  st.header("The Problem: Income Inequality πŸ’Έ")
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  st.write(
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  """
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+ Income inequality, a pervasive challenge that hinders economic progress and social well-being, demands innovative solutions. This app tackles this issue head-on, harnessing the power of machine learning to predict individual income levels.
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  **Key Challenges of Income Inequality:** ⚠
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  st.header("Solution πŸ’‘: Combating Income Inequality with Data-Driven Solutions πŸ“ˆ ")
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  st.write("""
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+ The app utilizes machine learning to predict individual income levels, providing valuable data to policymakers for informed action. This data-driven approach offers several advantages:
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  * **Cost-Effectiveness:** πŸ’°
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