Update README.md

README.md

@@ -14,3 +14,50 @@ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-
 
 Inspired by this video which discusses how Anthropic is studying how their model works using Dictionary Learning.
 https://youtu.be/AYTYk-kmXuI?t=168
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+Importing Libraries:
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+streamlit for creating the app.
+Scikit-learn (sklearn.decomposition.DictionaryLearning and datasets.load_digits) for dictionary learning and loading the dataset.
+matplotlib for plotting.
+numpy for numerical operations.
+Streamlit App Initialization:
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+The app sets a title and a description with st.title and st.write.
+Loading Data:
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+Digit data is loaded using load_digits(). This dataset contains 8x8 images of digits (0-9).
+Sample Image Display:
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+A slider is created with st.slider to select an index for displaying a sample image from the dataset using st.image.
+Selecting Number of Components:
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+Another slider allows users to choose the number of dictionary components (n_components) for dictionary learning.
+Performing Dictionary Learning:
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+DictionaryLearning is initialized with the selected number of components and fitted to the data.
+The dictionary elements learned are stored in dictionary.
+Displaying Dictionary Components:
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+The learned dictionary components are displayed as images using Matplotlib. Each component is reshaped into an 8x8 image.
+Displaying Sparsity:
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+Sparsity is calculated as the mean of zero entries in the transformed data (X_transformed) and displayed with st.write.
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+Assistant: Sure! The requirements.txt file is used to specify the dependencies needed for your Python project. For the Streamlit application demonstrating dictionary learning, you'll need the following libraries:
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+streamlit to create the interactive web app.
+scikit-learn for performing dictionary learning and loading the dataset.
+matplotlib for plotting the images.
+numpy for numerical operations.
+Here is a requirements.txt file that includes all these dependencies:
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+streamlit>=1.0.0
+scikit-learn>=0.24.0
+matplotlib>=3.0.0
+numpy>=1.19.0
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