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ayooshkathuria
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Ayoosh Kathuria ayooshkathuria

AI Researcher | Reinforcement Learning enthusiast looking for opportunities to use it products for consumers.

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ayooshkathuria/README.md

Hi, I'm Ayoosh!

AI Researcher & RL Practitioner diving deep into LLMs and exploring how RL can enhance them. Passionate about AI, optimization & making models smarter!

Work Experience

DRDO - Object detection for video surveillance in defense.
Pix2PixHD GAN - High-res image-to-image translation in MATLAB.
IIIT-Delhi - RL for mixed-autonomy traffic optimization.
Phaidra - RL for industrial cooling (Alpha Zero, MuZero, AWAC, PPO).

Notable Projects

Llama 3.2 - Fine-tuning from scratch on Alpaca-style datasets.
Computer Vision Augmentation Library - Bounding box augmentation for object detection.
PyTorch from Scratch - Step-by-step tutorial.

Writings

Paperspace Blog - AI articles
Medium - More of my work

Connect with Me

Email: kathuria.ayoosh@gmail.com
LinkedIn: Ayoosh Kathuria
X (Twitter): @KathuriaAyoosh

Always open to exciting AI collaborations & discussions!

Pinned Loading

  1. Llama-3.2-FT-From-Scratch-Alpaca Llama-3.2-FT-From-Scratch-Alpaca Public

    A project that implements Llama 3.2 from scratch and finetunes it on Alpca-style data.

    Jupyter Notebook

  2. pytorch-yolo-v3 pytorch-yolo-v3 Public

    A PyTorch implementation of the YOLO v3 object detection algorithm

    Python 3.3k 1k

  3. YOLO_v3_tutorial_from_scratch YOLO_v3_tutorial_from_scratch Public

    Accompanying code for Paperspace tutorial series "How to Implement YOLO v3 Object Detector from Scratch"

    Python 2.3k 719

  4. Paperspace/DataAugmentationForObjectDetection Paperspace/DataAugmentationForObjectDetection Public

    Data Augmentation For Object Detection

    Jupyter Notebook 1.2k 316

  5. Paperspace/PyTorch-101-Tutorial-Series Paperspace/PyTorch-101-Tutorial-Series Public

    PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.

    Jupyter Notebook 266 57

  6. kmeans_vectorised_v2.py kmeans_vectorised_v2.py
    1 import numpy as np
    2 import matplotlib.pyplot as plt
    3 import random
    4 import time
    5