Sentiment Analysis application
A sentiment analysis application that provides the user with features such as sentiment timeline, wordcloud, and other stats to better understand the review section of any selected product. It demonstrates the process by which I cleaned and analyzed the data and prepared it for machine learning application. The main application itself that uses the data and label developed by a prebuilt model. Lastly, a fresh logistic regression model trained on the data and evaluated in qualitative and quantitative manner. Both the pre-built and new model are testable in the app.
amazon-reviews-sentiment-analysis
Machine learning Demo web app
A Machine Learning demo data application using Streamlit and Python. It demonstrates three common ML algorithms that can predict the species of an iris flower when the user provides the features such as sepal length and width, and petal length and width. The classifiers used are the KNN model, the Naive Bayes model, and the Decision Tree model.
