We’re on a journey to advance and democratize artificial intelligence through open source and open science.| huggingface.co
Never store embeddings in a CSV!| minimaxir.com
Natural language processing (NLP) is a subfield of artificial intelligence (AI) that uses machine learning to help computers communicate with human language.| www.ibm.com
IMDb Non-Commercial Datasets| developer.imdb.com
We’re on a journey to advance and democratize artificial intelligence through open source and open science.| huggingface.co
We’re on a journey to advance and democratize artificial intelligence through open source and open science.| huggingface.co
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction| umap-learn.readthedocs.io
Topological Data Analysis and Simplicial Complexes| umap-learn.readthedocs.io
Database-like ops benchmark| duckdblabs.github.io
The goal of contrastive representation learning is to learn such an embedding space in which similar sample pairs stay close to each other while dissimilar ones are far apart. Contrastive learning can be applied to both supervised and unsupervised settings. When working with unsupervised data, contrastive learning is one of the most powerful approaches in self-supervised learning. Contrastive Training Objectives In early versions of loss functions for contrastive learning, only one positive a...| lilianweng.github.io
