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PROFESSIONAL EXPERIENCE
Project / Client Name / Location – Predictive model for PHM/ RNT/ Pune
Duration: May 2018 – Till Date
Technologies – Deep Learning, Python, Visualization
Project Profile:
1. The main objective is Fault diagnostics and disambiguation in the Electro Mechanical Actuators (EMA). To build
model for this kind of problem we need to preprocess the time series dataset which contains data of multiple
sensors of the system and build robust DAE model for detecting fault.
2. DAE model is implemented in Keras and to detect the fault we plotted Spider chart and for fault disambiguation
we used precision-recall matrix and ROC curve.
Role: Jr. ML Engineer
Contribution / Highlights:
❖ Data preprocessing, Model building and Spider chart.
Project / Client Name / Location – Visual Inspection/ RNT/ Pune
Duration: March 2018 – April 2018
Technologies –
Project Profile: This is the project for classifying the defects on the surface of the steel sheet. The model is built in
Keras and Convolution Neural Network is used for its architecture. For this we have also generated the images(by
rotating, flip etc.) and We have correctly classified all the test data and achieved almost 99% accuracy. After all this
the model is deployed on the website.
Role: ML Intern
Contribution / Highlights:
❖ Created the Pipeline, Built the Architecture in CNN
❖ Deployed model on the Server.
Project / Client Name / Location – Recommendation System/ RNT/ Pune
Duration: January 2018 – February 2018
Technologies – Machine Learning, Python
Project Profile: we built user-user and item-item collaborative filtering Recommendation System. For this we have
used Auto Encoder which is developed in Pytorch and KNN which is developed in Scikit-Learn and after building the
system we have deployed that on the server using Flask web-framework.
Role: ML Intern
Contribution / Highlights:
❖ Created an Auto-Encoder and KNN Model.
❖ Deployed on the Flask web-framework.
Project / Client Name / Location – Attendance System Using Face Recognition/ RNT/ Pune
Duration: December 2017 – December 2017
Technologies – Deep Learning, Python
Role: ML Intern
Project Profile: The objective of this project is to take attendance of the employees without their signature or thumb
impression. For this we Built a Face Recognition System which take employees real time images and recognize
their faces and use that for taking the attendance and update the database. We used Facenet’s prebuilt model to
train a model on our data.
Contribution / Highlights:
❖ Created a Dataset and training module.
❖ Created the SVM model for final classification.
Project / Client Name / Location – Website Development/ InnoEye Technology Pvt Ltd/ Indore
Duration: July 2017 – September 2017
Technologies – JavaScript, JQuery, AngularJS
Project Profile: The objective of the project is to build a website for the client. In this we have used AngularJS
framework, Java and Oracle database for backend.
Role: Intern
Contribution / Highlights:
❖ Created pages in AngularJS and JQuery.
❖ Deployed website on the TomCat Server.
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