PDF Chatbot: Query Textbooks for Subject Answers in English & Hindi
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Uses LSTM and Transformer models to predict asset returns and apply them in dynamic asset allocation and portfolio evaluation.
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Use hand movements to manage device settings like volume and brightness.
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Automated Diabetic Retinopathy detection using ResNet50, 96.17% training accuracy.
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Uses a content-based filtering approach to recommend movies similar to a user's favorite movie using NLP and cosine similarity.
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Uses machine learning and Logistic Regression to detect fake news articles by predicting the label of new unseen news.
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Predicts medical insurance costs based on features such as age, sex, BMI, children, smoker status, and region using Linear Regression.
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Uses the XGBoost regression model to predict house prices based on the California Housing dataset. It includes data preprocessing, EDA, model training, and evaluation.
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Uses the K-Means clustering algorithm to segment customers based on the Mall_Customers dataset. It includes data preprocessing, clustering, and visualization using plots.
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Uses Logistic Regression to predict the presence of breast cancer based on a dataset, classifying tumors as malignant or benign. The model has a training accuracy of 98% and a test accuracy of 96%.
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Uses the XGBoost gradient boosting algorithm to predict the number of calories burnt based on various exercise and demographic datasets. The model evaluates feature importance and performance.
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