access

Code to reproduce the experiments from the paper.

andrew-ng-machine-learning-notes

The offical notes of Andrew Ng Machine Learning in Stanford University

awesome-learning-with-label-noise

A curated list of resources for Learning with Noisy Labels

awesome-satellite-imagery-datasets

List of satellite imagery datasets with annotations for computer vision and deep learning

boss

This repository provides the code for replicating the experiments in the paper "Building One-Shot Semi-supervised (BOSS) Learning up to Fully Supervised Performance"

data-science-question-answer

A repo for data science related questions and answers

ddz16

dk_plotly

fast_text_gcn

FastGCN for inductive text classification

gbdxtools

Simple Python SDK for using GBDX.

graph-based-deep-learning-literature

links to conference publications in graph-based deep learning

graph_nets

PyTorch Implementation and Explanation of Graph Representation Learning papers involving DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

icassp19

Public repository for the paper "Learning Sound Event Classifiers from Web Audio with Noisy Labels"

imagecaptioning

jupyter

Jupyter metapackage for installation, docs and chat

llama2

machine_learning

mint-workflowdomain

A repository for storing and documenting the components used in WINGS workflows in the project

mit-deep-learning-book-pdf

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

model-agnostic-methods

Code to reproduce the experiments from the paper.

multimodal-exploration

prml

PRML algorithms implemented in Python

project1

pythonfromspace

Python Examples for Remote Sensing

random

resume

roaddetector

Winning Solutions from SpaceNet Road Detection and Routing Challenge

robosat

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water

sdm2023_graph_data_augmentation_tutorial

Materials for SDM 2023 tutorial: Augmentation Methods for Graph Learning

tayalkshitij