This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.
Estimating churners before they discontinue using a product or service is extremely important. In this ML project, you will develop a churn prediction model in telecom to predict customers who are most likely subject to churn.
The goal of this Spark project is to analyze business reviews from Yelp dataset and ingest the final output of data processing in Elastic Search.Also, use the visualisation tool in the ELK stack to visualize various kinds of ad-hoc reports from the data.
The project will use rasa NLU for the Intent classifier, spacy for entity tagging, and mongo dB as the DB. The project will incorporate slot filling and context management and will be supporting the following intent and entities. Intents : product_info | ask_price|cancel_order Entities : product_name|location|order id The project will demonstrate how to generate data on the fly, annotate using framework and how to process those for different pieces of training as discussed above .