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This project forked from labmlai/annotated_deep_learning_paper_implementations

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๐Ÿง  Minimal implementations/tutorials of deep learning papers with side-by-side notes; including transformers (original, xl, switch, feedback), optimizers(adam, radam, adabelief), gans(dcgan, cyclegan), reinforcement learning (ppo, dqn), capsnet, sketch-rnn, etc.

Home Page: https://nn.labml.ai

License: MIT License

Python 33.11% Makefile 0.06% Jupyter Notebook 66.83%

nn's Introduction

Kartik Sachdev

Mentor at Machine Learning for Science (ML4Sci) for Google Summer of Code (GSoC) 2024. Twice contributed to GSoC in 2023 and 2022. Graduate from RWTH Aachen University with MSc. Robotic Systems. Passionate about Robotics and Artificial Intelligence. Interests include:

  • Deep Learning
  • Computer Vision
  • Reinforcement Learning
  • Software development for robotic applications

โšก Projects

๐Ÿ”ง Technologies and Tools

python C++ ROS

MATLAB Git Linux

๐ŸŽ“ Certifications

Machine Learning Course, Stanford University

Logistic Regression, Supervised learning (Support Vector Machines, Neural Networks), Unsupervised learning (K-Means), Principal Components Analysis

Perception, University of Pennsylvania

Camera Modeling, Rotation & Translation, Projective Transformations, Feature Extraction, Pose Estimation & Random Sample Consensus (RANSAC) using MATLAB

Computational Motion Planning, University of Pennsylvania

Graph-based Plan Methods (Grassfire, Dijkstra's & A* Algorithm), Probabilistic Road Maps, Randomly Exploring Rapid Tress (RRTs) & Artificial Potential Field Methods using MATLAB

nn's People

Contributors

hnipun avatar keshsam avatar lc0 avatar sachdevkartik avatar vpj avatar

Stargazers

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