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In this project, we aim to identify different fruits: apples, bananas, oranges, and tomatoes; through different Machine Learning algorithms: CNN, XGBoost, InceptionV3 transfer learning, and VGG16 transfer learning
In this project we have created a spam classifier model on UCI dataset. We performed data cleaning and preprocessing, followed by Stemming and Bag of Words technique and finally developed a Naive Bayes Multinomial model.
TakenMind Global Internship Program is recognized under United Nations Sustainable Development and Growth (SDG) and is a highly recognized International Certification Program. - Reference Link to the United Nations SDG #26437 TakenMind Program. TakenMind (powered by United Nations SDG Program) is offering a Global Internship in Data Analytics an…
🗣️ Speech Type Detection is a Flask app to classifies text into categories like "Hate Speech," "Offensive Language," or "No Hate or Offensive Language" with 87.3% accuracy. It offers a user-friendly interface for text input and prediction, using machine learning algorithms. Idea for managing online inappropriate language. 🌐🔍.
Experience predictive healthcare with our Streamlit app. Utilizing Random Forest, our tool analyzes medical data to assess diabetes risk swiftly. Ideal for healthcare professionals and researchers, this user-friendly app simplifies risk evaluation. Join us in the fight against diabetes.