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Paras Kapoor

@paraskapoor

Data Scientist at Twyn

Noida, India

LinkedIn Profile

TwynGGDSD COLLEGE (Punjab University)

Paras Kapoor is a Data Scientist experienced in designing and implementing Machine Learning algorithms and predictive models to optimize operational efficiency. He specializes in using Machine Learning and Computer Vision, successfully deploying projects on edge devices like Jetson Nano and Raspberry Pi. His expertise includes developing end-to-end systems and creating front-end solutions using tools like Streamlit and Flask.

Experience

Data Scientist

Twyn

•Jan 2022 - Present•Noida, India

Deployed computer vision algorithms for a number of products: Wheel model inspection, Human Detection, QR Code scanner and generator, Cap Detection. Deploying Multi-functional Dashboard for different types of projects under the same roof based on computer vision. Implementing the state-of-the-art deep learning algorithms to solve defect detection problems in manufacturing. Responsible for developing end-to-end systems: data collection, evaluating different algorithms, deploying the solutions. Create front- end for the projects for better customer experience using Streamlit, Flask, flutter, kivy, tkinter. Building games in UNITY of the Smart Factories (Windows & mac) for user’s experience enhancement. Building AR based applications for the Smart Factories (Marker Based AR Applications). Reviewed Python code articles.

Data Science Intern

Rubixe

•Oct 2021 - Apr 2022•Bengaluru, India

Deployed various Machine Learning algorithms on different types of projects. Data Cleansing, Manipulation, Visualization, Training, Deployment using FLASK. Dashboards building using Tableau.

Education

GGDSD COLLEGE (Punjab University)

MSc Bioinformatics

Bioinformatics

Jul 2019 - Jul 2021•Grade: 84.15

GGDSD COLLEGE (Punjab University)

Bsc (Hons) Bioinformatics

Bioinformatics

Jul 2016 - May 2019•Grade: 75.43

Skills

Python
MYSQL
SQL server
Machine Learning
Computer Vision
Deep Learning
OpenCV
YOLO
CNN
RCNN
GIT
Streamlit
Flask
Tableau