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Pull Request for DL-Simplified 💡
Issue Title : Online Food Delivery Preferences
Closes: #793
Describe the add-ons or changes you've made 📃
Data Preprocessing:
-Removed missing and irrelevant data (e.g., 'Nil' reviews).
-Tokenized reviews and converted them into sequences suitable for deep learning models.
Exploratory Data Analysis (EDA):
-Analyzed the distribution of customer demographics such as age, income, family size etc.
-Created visualizations like bar charts and word clouds for reviews to understand sentiment polarity.
Model Implementation for Prediction:
-Built CNN, RNN, and RNN+LSTM models to predict customer reordering behavior.
-Experimented with different architectures to capture patterns in structured data.
Model Implementation for Sentiment Analysis:
-Developed DNN, LSTM, and GRU models for customer review analysis.
-These models were optimized to handle varying text lengths and interpret user sentiment effectively.
Evaluation and Comparison:
-Compared models using accuracy, precision, recall, and F1-score.
-Identified the most accurate models for each task.
Type of change ☑️
What sort of change have you made:
How Has This Been Tested? ⚙️
-Compared models using accuracy, precision, recall, and F1-score.
-Identified the most accurate models for each task.
Checklist: ☑️