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- ## Deep Prediction Hub
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- Overview
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- Welcome to Deep Prediction Hub, a Streamlit web application that provides two deep learning-based tasks: Sentiment Classification and Tumor Detection.
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- Tasks
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- 1. Sentiment Classification
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- This task involves classifying the sentiment of a given text into "Positive" or "Negative". Users can input a review, and the application provides the sentiment classification using various models.
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- 2.Tumor Detection
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- In Tumor Detection, users can upload an image, and the application uses a Convolutional Neural Network (CNN) model to determine if a tumor is present or not.
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- Getting Started
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- Prerequisites
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- Python 3.6 or higher
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- Required packages: streamlit, numpy, cv2, PIL, tensorflow
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- Pre-trained models: PP.pkl, BP.pkl, DP.keras, RN.keras, LS.keras, CN.keras
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- Trained IMDb word index: Ensure the IMDb word index is available for sentiment classification.
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- Installation
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- Clone the repository: git clone https://github.com/yourusername/deep-prediction-hub.git
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- Usage
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- Access the application by opening the provided URL after running the Streamlit app.
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- Choose between "Sentiment Classification" and "Tumor Detection" tasks.
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- Sentiment Classification
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- Enter a review in the text area.
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- Select a model from the dropdown.
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- Click "Submit" and then "Classify Sentiment."
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- Tumor Detection
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- Upload an image using the file uploader.
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- Click "Detect Tumor" to perform tumor detection.
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- Models
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- Perceptron (PP.pkl): Perceptron-based sentiment classification model.
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- Backpropagation (BP.pkl): Backpropagation-based sentiment classification model.
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- DNN (DP.keras): Deep Neural Network sentiment classification model.
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- RNN (RN.keras): Recurrent Neural Network sentiment classification model.
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- LSTM (LS.keras): Long Short-Term Memory sentiment classification model.
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- CNN (CN.keras): Convolutional Neural Network tumor detection model.
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- Contributing
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- Feel free to contribute by opening issues or submitting pull requests. Please follow the contribution guidelines.
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- License
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- This project is licensed under the MIT License - see the LICENSE file for details.
 
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+ ---
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+ title: DeepLearning
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+ sdk: streamlit
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+ emoji: 📈
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+ colorFrom: blue
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+ colorTo: blue
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+ pinned: false
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+ ---