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Hello, I'm Shubham Wagh 👨‍đŸ’ģ

Tech Enthusiast | Computer Vision Scientist


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🤔 About

  • Working : Mobile Robots 🤖 | Deep Learning đŸ’ģ | AWS ☁ī¸
  • Learning : Reinforcement Learning 🕹ī¸ | Blockchain đŸ’ģ | Guitar 🎸
  • Hobbies : Books 📚 | Music 🎧 | Ukulele đŸŽĩ
  • Ask me about : Anything!, I'm happy to help ✌ī¸
  • Pronouns : He/Him/His 😇

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⭐ī¸ From Shubham Wagh

Shubham Wagh's Projects

lucid icon lucid

A collection of infrastructure and tools for research in neural network interpretability.

mscthesis icon mscthesis

Learning Underwater Motion and 3D Reconstruction from Optical and Acoustic Sensors

nerf-toy icon nerf-toy

A 2D toy illustration of Neural Radiance Fields

netron icon netron

Visualizer for deep learning and machine learning models

opensfm icon opensfm

Open source Structure from Motion pipeline

openvslam icon openvslam

OpenVSLAM: A Versatile Visual SLAM Framework

paper-tips-and-tricks icon paper-tips-and-tricks

Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.

pcl icon pcl

Point Cloud Library (PCL)

picograd icon picograd

A lightweight neural network framework implementation in Python

py-image-dataset-generator icon py-image-dataset-generator

Image dataset generator intend to get a large image dataset with minimal effort by grabbing image through the web and generate new ones by image augmentation.

pypi_guide icon pypi_guide

A complete guide of how to upload your package to PyPi and make it installable using pip

python icon python

All Algorithms implemented in Python

python-pcl icon python-pcl

Python bindings to the pointcloud library (pcl)

pytorch-image-models icon pytorch-image-models

PyTorch image models, scripts, pretrained weights -- (SE)ResNet/ResNeXT, DPN, EfficientNet, MixNet, MobileNet-V3/V2/V1, MNASNet, Single-Path NAS, FBNet, and more

reinforcement-learning icon reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

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