Client wants to remove the approval process for the damaged products via images of the damaged products uploaded in chatbot.

Client wanted to classify the quotes which are potential to convert in orders.

A chatbot will be created for Siemens customers where they can upload images of their damaged products and the images of its details. If the algorithm finds it suitable for replacement then a replacement process will be triggered. This will eliminate the long approval process. If images are unable to recognized then a customer support person will be assigned directly.

This is my current project where we have different data frames(tables) from Account, Opportunity, Quotes and Orders. The data came from Salesforce CPQ module which was analyzed and found the potential customers who were actually interested in giving an order on a specified combination of products in a given Quotation for PSDO domain.

This project contained text data around 850MB which we have to analyze using Natural Language Processing techniques so that we can classify a tweet as Good, Bad, or Neutral.

We had the customer data from bank who had taken fixed deposits on considering various parameters of bank. So we had to predict weather a potential customer will take a Fixed Deposit in bank or not.

In this project we automized TOR(The Onion Router) browser which is used for deepnet websites so that it can download the websites which sell illegal stuff on internet like viruses and finding the vendor who most possible threat according to graph generated. Project was implemented in Java using Eclipse and database used is Mysql.

This project is all about Package Delivery Management. Its a project where a user can upload their packages those packages would be transferred in bags(bags can have multiple packages) and those bags will be transferred to vehicles(a vehicle can have multiple bags) which is ready for dispatch , all packages , bags and vehicle has various stages of lifecycle which each has to undergo.