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MTECH Scholar | Data Engineer
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Punjab Engineering College
Data Scientist
June 16, 2026 – Present
Covid19-Vaccine-Twitter-Sentiment-Analyis
April 20, 2021 – April 20, 2021
Covid19-Vaccine-Twitter-Sentiment-Analyis — GitHub repository
View ProjectExploring-the-Bitcoin-Cryptocurrency-Market
April 3, 2021 – April 20, 2021
To better understand the growth and impact of Bitcoin and other cryptocurrencies and explore the market capitalization of different cryptocurrencies.
View ProjectCSV_2_JSON_string
February 28, 2021 – February 28, 2021
Convert CSV file to JSON string with single tap
View ProjectDataCamp-Project-Real-time-Insights-from-Social-Media-Data
January 17, 2021 – January 17, 2021
In this Project, you will use pre-downloaded datasets to understand the nuts and bolts of Twitter Data.
View ProjectClassify-song-genres-using-audio-data
August 29, 2020 – September 3, 2020
Classify-song-genres-using-audio-data — GitHub repository
View ProjectTechnocolabs-Internship-Project
August 2, 2020 – August 27, 2020
Technocolabs-Internship-Project — GitHub repository
View ProjectDice-Roll-Game
July 16, 2020 – July 16, 2020
Creating a dice roll simulation Using Python and tkinter
View ProjectStress-detection-Techniques-and-Chat-Bot-Depression-Therapy
June 13, 2020 – June 22, 2022
The Real time emotion recognition model will return the emotion predicted in real time. The model classifies face as stressed and not stressed. A model is trained on the fer2013 dataset (https://www.kaggle.com/deadskull7/fer2013) .The stress level is calculated with the help of eyebrows contraction and displacement from the mean position. The distance between the left and right eyebrow is being calculated and then the stress level is calculated using exponential function and normalized between 1 to 100. Chatbot-Depression Therapy to provide real time therapeutic solutions to alleviate depression. Chatbot System is implemented using deep learning for detection and management of stress and depression and provide suggestions accordingly based on user’s mental condition. Technologies: Keras, genism python libraries, anaconda environment, the dataset being used is obtained from Kaggle.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards personal learning and exploration in data science. The diversity of projects (sentiment analysis, emotion recognition, cryptocurrency analysis) suggests curiosity and a willingness to tackle different problem domains. However, the lack of team-based projects or contributions to open-source initiatives makes it difficult to assess collaboration and broader cultural fit within a professional team setting.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's projects indicate an ability to work independently on self-directed tasks.