Vaibhav K.

Vaibhav K.

Microsoft technology expertise with healthcare domain

Ghaziabad , India

Experience: 11 Years

Vaibhav

Ghaziabad , India

Microsoft technology expertise with healthcare domain

35103.8 USD / Year

  • Start Date / Notice Period end date: 2021-09-30

11 Years

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About Me

  • A result-oriented professional with over 8+ years’ experience in application development & enhancement, service delivery and client interaction.
  • Last 2+ years working on Supervised Machine learning for regressio...
  • Last 2+ years working on Supervised Machine learning for regression and classification problems and Artificial Intelligence.
  • Last 2+ years working on Chat-bot with Supervised Machine learning using Microsoft Cognitive service and Custom development.
  • Working on CNN (Convolutional neural network) problem i.e. Image Processing and Image Recognition.
  •  3+ years of experience in HEALTH CARE DOMAIN.
  • Worked with ERP, FMCG and Finance domain.
  • Insightful knowledge of Microsoft technology, MVC, WCF, MVC, Bootstrap, ASP.NET and ADO.NET, Relational database i.e. SQL.
  • Team leading client interaction and delivery Experience.
  • Worked on Agile methodology Scrum and sprints.

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Portfolio Projects

: Image Recognition (CNN)

Image Processing to identify with existing Image from live capture image or from

Company

: Image Recognition (CNN)

Role

Full-Stack Developer

Description

Image Processing to identify with existing Image from live capture image or from video from Video we iteration each and every frames from the existing one. While getting the frame first identify only human images and extract each and every frame approximate 30 frames in a sec. After extract the frame we identify each and   every image from frame and check with existing one we get the match image details we stop the thread.
This system is associated with one of our visitor management system to identify the visitor  is already visit the organization and pop up all the details of visitor if no match found we get the details in our DB for next time.
My Role & Responsibilities as a Team Member:    
Design the architecture of application.
Develop the Pipeline and algorithm.
Design & Development Client Side Coding SQL Script, Jobs.
 

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Skills

Python

Chat-bot with Prediction model

Company

Chat-bot with Prediction model

Description

Description:  Chat-bot program designed to simulate conversation with human users, especially over the Internet. Chatbot is communicating like human. Once user ask some query related to specific area it will respond like human get query and calculate the intention as well as entities and try to get proper response from either DB or from FAQ’s once bot respond after calculation.

Chat-bot can manipulate the query if intention is not clear based on synonyms once synonyms get from grammar package custom pipeline use some algorithms with some custom logic as through  KNN algorithm and get proper response.

This Chat-bot will work based on supervised learning with regression algorithm.

 

Working on Prediction model on the basis of precision and recall basis. Because of the problem is to get the probability the how many employees can leave the organization in next few months and which employee is going to leave. We used two vector machine algorithms to fix this classification problem. Basis on previous year data model will prepare and trained after training model is ready to validate the employee database.

 

My Role & Responsibilities as a Team Member:          

  • Design the architecture of application.
  • Develop the Pipeline and algorithm.
  • Design & Development Client Side Coding SQL Script, Jobs

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Skills

Python C Sharp SQL

Tools

Python

Chat-bot

Company

Chat-bot

Description

Description:  Chat-bot is for resolve to all HR related query without the intervention of human. Chat-bot is communicating like human. Once user asks some query related to specific area it will respond like human.

Chat-bot first query to QNA Maker and gets the response from there else same query ask with LUIS. After getting the response from LUIS and check the high scoring Intent and pursue to user.

All intent and entities will create LUIS. And in QNA create the request and responses.

We have used Text Analytics API (NLP) for named entity and key phases also getting response from this API to sentiment analysis.

 

My Role & Responsibilities as a Team Member:          

Design the architecture of application.

Design & Development Client Side Coding and create intent entirety phases.

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Skills

C Sharp

EDGE

Company

EDGE

Description

Description: 

  • EDGE is resource management system.
  • Main Facilities available in this Project are:

ü Maintaining all records of employee as well as all projects those are running inside the organization or new projects with all levels like bid, bid win, bid loss, contract sign etc..

ü Automatic notifications if employee is going to release from project.

ü Capture Employee information from third party if employees need to select employee for specific skills set.

  • This System has many modules like Resource Request, Approvals, Searching skills set (Internally or externally), Bidding information and Status etc. if organization get any project contract and needs to build a team for specific skill set either internally or externally first project manager creates resource request based on required skills set and check number of requirement which needs to full fill from either resource bench or hiring new employee from market after the approvals build the team from resource bench or future release from others projects attached the resume using search the candidate for specific skill-set entered by employee in his resume (using third party tool based on DAT file) this is for internal employee. After that we attached n number of resume on send for the interview. After selection of employee request will automatically close. If skills set is not matched with internal will pick resume from third party application or other employment sites which we have already integrated with employment sites.

 

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