Summary
Work History
Education
Skills
Accomplishments
Profile
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Soubhagya Nayak

Soubhagya Nayak

Fresher
Bhubaneswar,OR

Summary

Highly focused to obtain an entry-level Software Engineer position and applying my problem-solving and technical skills to develop business applications.

Work History

Intern

Ineuron
09.2021 - 11.2021

.

  • Developed Google Analytics customer Revenue Prediction System Gained exposure in end-to-end development of Machine Learning products, from requirement analysis to designing, data gathering, preprocessing, feature engineering, coding, Ops pipeline, and deployment.
  • LightGBM model used for prediction which has less MSE 1.021 than other algorithm . Dataset was quite huge so it helped to reduces memory usage

Education

Computer Science And Information Technology

C V Raman Global University
06.2018 - 04.2022

Skills

    Problem Solving

Data Structure

Django

Flask

JavaScript

Machine Learning

Deep Learning

Computer Vision (OpenCV)

NLP (NLTK, Spacy)

Database Management (MySQL/MongoDB))

Accomplishments

  • Assisting Vision For Blinds (06/2021 - 11/2021) Worked on Assisting Vision for visually impaired people using [Python/Deep Learning, Computer Vision, Ajax, Flask, AWS S3]. Inception V3 network used for feature extraction and Embedding layers for vectorization and LSTM network for text sequence generation. gtts library for text to speech conversion. Machine translation is used for different regions peoples https://github.com/Soubhagya264/Image_cap_visually_impared
  • Movie Recommendation System with Reviews Sentiment Analysis (12/2020 - 03/2021) Worked on Movie Recommendation System with Reviews Sentiment Analysis. The core recommendation engine developed by cosine similarity Performed key role in the development process of Both Backend(Flask) and Frontend(JavaScript) of the web application.
  • Wafer Fault Detection (04/2021 - 06/2021) Built Wafer Fault Detection using Machine Learning Provided system maintenance and support procedures for log files update, database tables, and stored procedures. We have compared two models xgboost and randomforest . random forest have high AUC score (0.5) than Xgboost so i have used random forest model. https://github.com/Soubhagya264/Wafer_Project/
  • Food Delivery App With Ai Bot (09/2020 - 12/2020) Worked on Food Delivery App] using[Python/ Django , JavaScript, TensorFlow , NLTK] Worked with Django Framework for backend, TensorFlow for AI Bot model, NLTK for preprocessing, JavaScript for event handling. https://github.com/Soubhagya264/Food_App

Profile

LeetCode : https://leetcode.com/Soubhagya264/

GitHub : github.com/Soubhagya264

LinkedIn : linkedin.com/in/soubhagya-nayak-1a174518b

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