Hemanth S Banur

Machine Learning & MLOps Enthusiast

Profile Picture

Summary

Passionate Machine Learning and MLOps enthusiast with a strong foundation in Computer Science. Experienced in developing ML models, implementing MLOps practices, and creating web applications.

Skills

Languages:

C/C++, C#, Python, JavaScript, TypeScript, MATLAB, HTML, CSS

Libraries:

Pandas, Numpy, Scikit-Learn, OpenCV, PyTorch, TensorFlow, Matplotlib, Seaborn, NLTK

Frameworks/Tools:

Docker, React.js, Node.js, MongoDB, Git, Unity, Azure, mlflow, ZenML, Flask, Dagshub, Firebase, Django, Flutter, Linux

Education

PES University

Nov 2022 - Present

Bangalore, India

B.Tech in Computer Science and Engineering

Experience

IEEE CS, PES University

Open Source Project Initiative

Jul 2024 - Aug 2024, Part-time

Bangalore

  • Developed a hybrid GAN-VAE architecture for artistic style transfer
  • Approached in cyclic GAN, Attention GAN, Autoencoders, hybrid VAE-GAN

Toyota Kirloskar Motor

Data Science Intern

Jun 2024 - Jul 2024, Full-time

Bangalore, India

  • Developed an automated web scraping and review analysis system using NLTK, used by all the employees reducing manual work time from 6-7 hours to 8-10 seconds
  • Built a system for real time remote data analysis, cutting down manual work time from 4-5 hours to 5-10 seconds
  • Deployed all my projects on LAN and made available for all the employees

CDSAML, PES University

Research Intern

Jun 2024 - Jul 2024, Part-time

Bangalore

  • Developed a multi-modal pipeline for converting Kannada speech to English Text
  • Stages involving Audio denoising, Enhancing, segmenting, Transcripting, Punctuating, Translating, Grammar checking
  • User can edit the output of each stage or let as it is, so that it's fed as input for successive stage

Projects

Cropify

Cropify is a web application built using React.js, Flask & Machine learning models in the backend

ReactJSFlaskscikit-learnkeras

MLOps

1. Credit Card Fraud Detection 2. Customer Satisfaction. Used pipelining, DagsHub, ZenML, mlFlow

dagshubmlflowpython

Machine Learning

1. Wine quality 2. Kidney disease classification. Data Ingestion, Data Validation, Data Transformation, Model Training, Prediction Pipeline

scikit-learndvcpython

Reg-Model

Built a Regression model for a particular dataset with all the statistical analysis

Data Analysisscikit-learnpython

Zombie v/s player 3D

An Unity Developed 3D game

UnityC#

Activities & Achievements

Practical Approach to ML

Won 1st place in the hackathon organised by CIE PESU held for 4 weeks (Apr 2024)

Appex | Technical Lead

Organised "AppGenesis," an ideation event, served as a mentor for the same, providing guidance and support to participants throughout the event

Aura | Technical member

Organized "Crayion", a hackathon event focused on image generation using advanced models such as DALL-E and Midjourney