Neural networks training pipeline based on PyTorch

My repo for training neural nets using pytorch-lightning and hydra

Curriculum training

YOLOv12 Underwater Object Detection is an open-source suite for underwater object detection, built on YOLOv12. It offers an end-to-end pipeline with GPU-accelerated training, customizable data augmentations, real-time inference via Gradio, and support for model export (ONNX & PyTorch).

Train custom wake word models with openWakeWord. A granular 13-step pipeline with compatibility patches for torchaudio 2.10+, Piper TTS, and speechbrain. Generates tiny ONNX models (~200 KB) for real-time keyword detection — like building your own "Hey Siri" trigger. WSL2/Linux + CUDA required.

tracebloc notebook to launch and manage experiments in collaboration

End-to-end speech model training pipeline built on Burn — MFCC features, CTC loss, LibriSpeech loader, SpeechOcean762 evaluation

Deep Learning training and deployment pipeline, reduce repetitive work from research to deployment

This repository features an image sharpening pipeline using Knowledge Distillation. A high-capacity Restormer acts as the teacher model, while a lightweight Mini-UNet is trained as the student to mimic its performance.

Immutable checkpoint storage for ML training pipelines. Kernel-level protection, anomaly detection, score-gated rollback, and self-healing recovery. Built in Rust.

Training an image classification model with CIFAR-10 dataset

🧠 Deep-Learning Evolution: Unified collection of TensorFlow & PyTorch projects, featuring custom CUDA kernels, distributed training, memory‑efficient methods, and production‑ready pipelines. Showcases advanced GPU optimizations, from foundational models to cutting‑edge architectures. 🚀

YOLO training toolkit with Claude Code skills — dataset management, experiment tracking, HP tuning via model.tune(), active learning with CVAT, ONNX export. Supports YOLO11 & YOLO26.

SPIRA Model Trainer v2 (redesigned pipeline) by @danlawand

Machine Learning in Production

Internship projects completed as part of the Shristi24 program offered by IIIT Hyderabad

Desktop GUI app for automating deep learning training on Vast.ai cloud GPUs — classification & regression with one click

AI Message Labels: Packaging and pipelines for deep learning text classification models

PyTorch detailed analysis to create Machine learning to Deep learning model

Configurable PyTorch training pipeline