Tableau

DECEMBER 1, 2021

IPO in 2013. Tableau had its IPO at the NYSE with the ticker DATA in 2013. Even modern machine learning applications should use visual encoding to explain data to people. Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. Release v1.0 Query innovation.

Tableau 98

Tableau ML ML Database 98

Mlearning.ai

APRIL 1, 2023

It was first introduced in 2013 by a team of researchers at Google led by Tomas Mikolov. Word2Vec is a shallow neural network that learns to predict the probability of a word given its context (CBOW) or the context given a word (skip-gram). For this, Top2Vec utilizes a manifold learning technique called UMAP.

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Clustering 52

Towards AI

APRIL 8, 2024

Developed by researchers at Google in 2013 [1], Word2Vec leverages neural networks to learn dense vector representations of words, capturing their semantic and contextual relationships. At its core, Word2Vec is based on the distributional hypothesis, which states that words occurring in similar contexts tend to have similar meanings.

Natural Language Processing 81

Natural Language Processing Clustering Algorithm AI 81

Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., an image) with the intention of causing a machine learning model to misclassify it (Goodfellow et al., 2013; Goodfellow et al.,

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

PyImageSearch

OCTOBER 2, 2023

VAEs were introduced in 2013 by Diederik et al. They extended the idea of autoencoders to learn useful data distributions. It serves as a direct drop-in replacement for the original Fashion-MNIST dataset for benchmarking machine learning algorithms, with the benefit of being more representative of the actual data tasks and challenges.

Deep Learning 120

Deep Learning Deep Learning Clustering Computer Science 120

Hacker News

APRIL 18, 2024

You can find it in the turning of the seasons, in the way sand trails along a ridge, in the branch clusters of the creosote bush or the pattern of its leaves. In such perfection, all things move toward death.” ~ Dune (1965) I find the concept of embeddings to be one of the most fascinating ideas in machine learning.

Natural Language Processing 107

Natural Language Processing Clustering Machine Learning Machine Learning 107

ML Review

MARCH 5, 2019

For instance, consider the sentence “ I like machine learning ” and a context window of size 1. Then, the words which give context, or appear in the context window around the word “ machine” , are “ like ” and “ learning ” (the window is considered both on the left and on the right). References Harris, Z. Mikolov, T.,

AI 40

AI AI Clustering Machine Learning 40

DrivenData Labs

DECEMBER 7, 2023

In the Unsupervised Wisdom Challenge , participants were tasked with identifying novel, effective methods of using unsupervised machine learning to extract insights about older adult falls from narrative medical record data. Solution format. However, it wasn't the use of sophisticated tools alone that made for strong submissions.

Natural Language Processing 130

Natural Language Processing Clustering Data Science Data Analysis 130

Pickl AI

FEBRUARY 23, 2025

Apache Hadoop Apache Hadoop is an open-source framework that allows for distributed storage and processing of large datasets across clusters of computers using simple programming models. It is designed to scale up from a single server to thousands of machines. Durability: Messages are stored on disk and replicated within the cluster.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52