This code is used to build & run a Docker container for performing predictions against a Spark ML Pipeline.

This project demonstrates how parallel reasoning branches, multi-round refinement, and self-consistency voting can dramatically improve reasoning accuracy on a 3B parameter model.

This project is an app that lets the user control the mouse pointer of their computer using their eye gaze. The app uses multiple pre-trained computer vision models from the openvino model zoo in a structured pipeline to detect the user's eye gaze and move the mouse pointer in the right distance and direction.

Using web scraped data from one of India's largest car website, Cardekho, building a prediction service with feature, training and inference pipelines.

YOLO Model Training and Inference Pipeline with Streamlit

WASB-SBDT-FPFilter 是一个可配置、工程化的体育球（网球/足球/羽毛球/排球/篮球）检测与跟踪基线实现，基于 WASB。仓库包含评估代码、示例数据、预训练权重、FP（假阳性）过滤训练与推理工具、交互式 patch 标注工具，并新增了一个一键式端到端推理 Pipeline（WASB 检测 → FP 过滤 → 可视化）。支持通过 Hydra 配置灵活定制，适合研究与工程化部署场景。

Neural network implementations from scratch

Public entry point for the AxonOS project — an open operating layer for brain-computer interfaces.

This project is a handcrafted end-to-end Optical Character Recognition (OCR) pipeline built to transcribe my handwritten journal entries into digital text—using PyTorch, Faster R-CNN, AWS Lambda, and iOS Shortcuts. It's a personal and technical showcase of deep learning, MLOps, and full-stack AI deployment. Includes in-depth technical report.

FastAPI Wrapper for V2 Inference Protocol

A scalable demand forecasting system implementing automated retraining, MLflow-based model management, and cloud deployment using production-grade MLOps practices.

Hourly pipeline that discovers, fetches, and classifies engineering jobs from company ATS boards — publishes a curated index to builder-jobs.

An end to end prediction service for flagging credit card fraud.

Fine-tuned TinyLlama using LoRA on a custom FastAPI Q&A dataset to create a specialized domain expert model. Includes dataset prep, LoRA training script, inference interface, and Colab-ready workflow.

Production-ready GenAI inference and SOTA evaluation pipeline. Generates legally robust patent claims using CoT prompting and benchmarks them via an automated LLM-as-a-Judge R&D loop.

Acquiring inference analytics from the fine-tuned YOLOv11s and making a data lake-warehouse out of that inferences on PostgreSQL DB.

A deployment-ready regression pipeline predicting health insurance costs, featuring segmented modeling and an inference-only Streamlit architecture to prevent runtime data leakage.

Secure, multi-VM cross-language inference architecture orchestrated over WebSocket RPC using the iii engine. Fully automated with Terraform (VPC, private subnet isolation, NAT Gateway) and systemd services.