martinetoering

3D-ResNets-PyTorch-TimeCycle

Video classification project using 3DCNNs and multiple self-supervised pretraining tasks (June, 2018).

certified-robustness-benchmark

CLIP

Contrastive Language-Image Pretraining

Deep-Learning

Deep Learning methods using MLPs, CNNs and Backpropagation, RNNs, and Deep Generative Models (November, 2019).

deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

KRR-course

Projects on symbolic systems, covering logic and problem solving (June 2020).

ml-demo-fastapi-k8s

The project is a machine learning (ML) deployment tutorial and MLOps practice. It deploys a video classification model trained on Kinetics-400 as a simple FastAPI app to Kubernetes with minikube.

ViCC

[WACV'22] Code repository for the paper "Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting", https://arxiv.org/abs/2106.10137.

video-ml-training

This repository serves as an example training pipeline for ML projects. It implements the computer vision task of video classification training on K400-Tiny (a sample subset of Kinetics-400).

Visual-Representation-Learning-Tutorials

Project materials for teaching bachelor students about fundamentals on Deep learning, PyTorch, ConvNets & Autoencoder (January, 2021).

martinetoering/ViCC

[WACV'22] Code repository for the paper "Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting", https://arxiv.org/abs/2106.10137.

martinetoering/ml-demo-fastapi-k8s

The project is a machine learning (ML) deployment tutorial and MLOps practice. It deploys a video classification model trained on Kinetics-400 as a simple FastAPI app to Kubernetes with minikube.

martinetoering/video-ml-training

This repository serves as an example training pipeline for ML projects. It implements the computer vision task of video classification training on K400-Tiny (a sample subset of Kinetics-400).

martinetoering/3D-ResNets-PyTorch-TimeCycle

Video classification project using 3DCNNs and multiple self-supervised pretraining tasks (June, 2018).

martinetoering/Deep-Learning

Deep Learning methods using MLPs, CNNs and Backpropagation, RNNs, and Deep Generative Models (November, 2019).

martinetoering/KRR-course

Projects on symbolic systems, covering logic and problem solving (June 2020).

martinetoering/Visual-Representation-Learning-Tutorials

Project materials for teaching bachelor students about fundamentals on Deep learning, PyTorch, ConvNets & Autoencoder (January, 2021).

martinetoering/certified-robustness-benchmark

martinetoering/CLIP

Contrastive Language-Image Pretraining

martinetoering/deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

martinetoering/detectron2

Detectron2 is FAIR's next-generation platform for object detection, segmentation and other visual recognition tasks.

martinetoering/DQN_Divergence

Reinforcement Learning Project studying the divergence of Deep Q-Learning Networks.

martinetoering/Machine-Learning-1

Machine Learning Projects on Linear Regression, Classification and Multi-layer Perceptrons, and Gaussian Processes and SVMs (October, 2019).

martinetoering/Embetter

FACT-AI (Fairness, Accountability, Confidentiality, and Transparency in AI) Project on Debiasing word embeddings

martinetoering/fastbook

The fastai book, published as Jupyter Notebooks

martinetoering/FoodTrucks

:truck: San Francisco's finger-licking street food now at your fingertips.

martinetoering/involution

[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator

martinetoering/leetcode

All Python solutions for Leetcode

martinetoering/Machine-Learning-2

Projects from the Machine learning 2 Course on ICA, Inference in Graphical models, EM algorithm and VAE (October, 2020).

martinetoering/ML-From-Scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

martinetoering/Probability-Theory-For-ML

Probability Theory for Machine Learning, including probability fundamentals, distributions and Bayesian inference (October, 2018).

martinetoering/python-mastery

Advanced Python Mastery (course by @dabeaz)

martinetoering/PythonOOP

The Original Code repository for my Python OOP Series

martinetoering/pytorch-tutorials

PyTorch tutorials.

martinetoering/Reinforcement-Learning

Reinforcement Learning Projects on Dynamic Programming, Monte Carlo and Deep Q-Networks (October, 2020).

martinetoering/shannon-switching-game

Implementation of Shannon switching game, a two-player connection game on an undirected graph.

martinetoering/SimilArt

Information visualization project on SimilArt, a platform for exploring and comparing artworks.

martinetoering/SlowFast

PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.

martinetoering/swav

PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

martinetoering/vnncomp2021

VNN Neural Network Verification Competition 2021