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Update pages/6_Feature_Engineering.py

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  1. pages/6_Feature_Engineering.py +15 -17
pages/6_Feature_Engineering.py CHANGED
@@ -81,42 +81,41 @@ st.markdown("<h1 class='header-title'>πŸ› οΈ Feature Engineering πŸ“Œ</h1>", un
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  st.markdown(
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  """
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  <div class='info-box'>
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- <p>πŸ”Ή When we take **existing features** from collected data and create **new useful features**,where this is automatically engineered made from existing features and the technique of creating the features is known as <span class='highlight'>Feature Engineering</span>.</p>
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- <p>πŸ“Š These engineered features **enhance machine learning models**.</p>
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- <p>πŸ“ A subpart of feature engineering is **Feature Extraction**.</p>
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  </div>
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  """,
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  unsafe_allow_html=True
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  )
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- st.markdown("<h2 class='sub-header'>πŸ“₯ Feature Extraction</h2>", unsafe_allow_html=True)
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-
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  st.markdown(
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  """
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  <div class='info-box'>
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- <p>πŸ“ **Feature Extraction** is the process where text data which is natural language is given to machine to understand the natural language.</p>
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  <ul>
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- <li>πŸ“œ Text is **converted into vectors** using specific algorithms.</li>
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- <li>πŸ” **Preserving meaningful information** is key.</li>
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- <li>βš™οΈ Helps in better **text analysis & machine learning**.</li>
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  </ul>
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  </div>
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  """,
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  unsafe_allow_html=True
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  )
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- st.markdown("<h1 class='header-title'>🧭 Vectorization</h1>", unsafe_allow_html=True)
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  st.markdown(
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  """
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  <div class='info-box'>
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- <p>πŸ“Œ **Vectorization** is the process of converting text into **numerical vectors**.</p>
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- <p>πŸ’‘ This allows ML models to process text data effectively.</p>
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  </div>
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  """,
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  unsafe_allow_html=True
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  )
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- st.markdown("<h2 class='sub-header'>πŸ› οΈ Vectorization Techniques</h2>", unsafe_allow_html=True)
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  st.markdown(
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  """
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  <div class='info-box'>
@@ -130,15 +129,14 @@ st.markdown(
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  """,
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  unsafe_allow_html=True
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  )
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-
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  st.markdown(
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  """
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  <div class='info-box'>
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  <p>πŸš€ Advanced Vectorization Techniques:</p>
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  <ul>
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- <li>🌍 Word Embeddings</li>
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- <li>πŸ”  Word2Vec</li>
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- <li>⚑ FastText</li>
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  </ul>
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  </div>
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  """,
 
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  st.markdown(
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  """
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  <div class='info-box'>
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+ <p>πŸ”Ή When we take existing features from collected data and create new useful features, where this is automatically engineered made from existing features and the technique of creating the features is known as <span class='highlight'>Feature Engineering</span>.</p>
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+ <p> These engineered features enhance machine learning models.</p>
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+ <p> A subpart of feature engineering is Feature Extraction.</p>
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  </div>
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  """,
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  unsafe_allow_html=True
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  )
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+ st.subheader(":violet[Feature Extraxtion]")
 
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  st.markdown(
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  """
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  <div class='info-box'>
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+ <p>πŸ“ Feature Extraction is the process where text data which is natural language is given to machine to understand the natural language.</p>
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  <ul>
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+ <li>Text is converted into vectors using specific algorithms.</li>
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+ <li>Preserving meaningful information is key.</li>
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+ <li>Helps in better text analysis & machine learning</li>
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  </ul>
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  </div>
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  """,
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  unsafe_allow_html=True
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  )
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+ st.header("Vectorization🧭")
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  st.markdown(
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  """
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  <div class='info-box'>
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+ <p>Vectorization is the process of converting text into vector.</p>
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+ <p>This allows ML models to process text data effectively.</p>
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  </div>
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  """,
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  unsafe_allow_html=True
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  )
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+ st.subheader("Vectorization techniques")
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  st.markdown(
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  """
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  <div class='info-box'>
 
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  """,
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  unsafe_allow_html=True
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  )
 
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  st.markdown(
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  """
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  <div class='info-box'>
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  <p>πŸš€ Advanced Vectorization Techniques:</p>
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  <ul>
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+ <li>πŸ”Ή Word Embeddings</li>
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+ <li>πŸ”Ή Word2Vec</li>
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+ <li>πŸ”ΉFastText</li>
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  </ul>
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  </div>
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  """,