Available for opportunities

Saurabh
Vishwakarma

ML Engineer & Data Scientist — building intelligent systems that turn complex data into real-world impact.

3+// years coding
10+// ML projects
20+// skills
Saurabh Vishwakarma
01 — about me

The human behind
the models

I'm a passionate ML Engineer pursuing a BCA at Chandigarh University alongside a B.S. in Data Science & Applications from IIT Madras — a dual pursuit that shapes how I think about both engineering and mathematics.

My focus is on developing production-ready machine learning systems — from data pipelines to deployment — using Python, TensorFlow, PyTorch, and modern MLOps tooling.

Whether building predictive models, experimenting with LLMs, or crafting RAG systems, I'm driven by one goal: making AI genuinely useful.

🎓
Chandigarh University
BCA — Bachelor of Computer Applications
🏛
IIT Madras
B.S. in Data Science & Applications
// Languages
PythonCC++JavaScriptHTMLCSS
// ML / AI
TensorFlowPyTorchscikit-learnCNNsLLMsNLPRAGTransformersDeep Learning
// Data
NumPyPandasMySQLMongoDB
// DevOps & Tools
Git / GitHubLinuxDockerKubernetesMLflowFlaskFastAPI
02 — projects

Things I've built

001
LeafLens: Image Super resolution

AI-powered plant image super-resolution system built using SRGAN-style deep learning architecture for enhancing low-resolution leaf images into high-quality outputs.

Python Fast-Api Docker SRGAN Pytorch
Live ↗
002
ATS Intelligence Engine

An AI-powered full-stack web app that analyzes resumes against job descriptions using LLM-based semantic analysis to generate ATS-focused feedback and skill gap insights.

Python Flask Docker NLP LangChain
Live ↗
003
House Price Predictor

A full-stack ML application that predicts housing prices using linear regression, served via a Flask REST API and deployed on Render with a clean web interface.

Python Flask Linear Regression scikit-learn
Live App ↗
004
Sentiment Analysis Engine

An NLP pipeline that classifies text sentiment using NLTK and natural language processing techniques.

Python NLP NLTK
In progress
005
GRU from Scratch for Text Generation

Model trained on Amazon review data to generate coherent sequential text using GRU architecture.

Python PyTorch
View Source ↗
03 — mini models

Bite-sized ML
experiments

A collection of focused machine learning models — each one built to explore a concept, test an algorithm, or solve a small real-world problem. Browse them all on GitHub.

🩸
Diabetes Detector
Predicts the likelihood of diabetes in women using medical diagnostic features.
scikit-learn
🛒
E-Commerce Text Classification
NLP-powered Text classifier using Naive Bayes and TF-IDF features.
NLP · scikit-learn
📰
Fake News Classification
Classification system using pre-trained word embeddings from spaCy.
SpaCy · sklearn
🔢
HandWritten Digit Classification
Handwritten digit classification using a neural network model.
CNN
View all mini models on GitHub ↗
04 — contact

Let's work together

Open to ML engineering roles, research collaborations, and interesting projects.

Status
Available for opportunities