NLP and Forecasting Models were deployed on Streamlit with Python and hosted through Heroku
Summarizer-AI: link
Both NLP summarizers were used in this section such that the user can summarize relevant articles by inputting a search term or summarize a specific article by inputting a URL. The search query will output a list of articles and the top 2 will be summarized based on relevancy to the topic. The article’s text will be extracted and sent to the model which will summarize it based on the given complexity.
Analyzing and Forecasting Data: link
Data Forecasting system deployed with interactive charts for visualization and extrapolation of information through data models. Graphing tools include various features to customize the analysis process and charts can be saved a .png or .jpg
The training and testing process of the ML Models can be viewed on the Construction repository.