AWS Machine Learning Blog

MARCH 15, 2024

Solution overview We deploy FedML into multiple EKS clusters integrated with SageMaker for experiment tracking. EKS Blueprints helps compose complete EKS clusters that are fully bootstrapped with the operational software that is needed to deploy and operate workloads. He also holds an MBA from Colorado State University.

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Mlearning.ai

APRIL 1, 2023

It was first introduced in 2013 by a team of researchers at Google led by Tomas Mikolov. Image taken from Efficient Estimation of Word Representation in Vector Space Top2Vec Top2Vec is an unsupervised machine-learning model designed for topic modelling and document clustering. To achieve this, Top2Vec utilizes the doc2vec model.

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Flipboard

OCTOBER 16, 2023

Nagle’s brain implant, developed by the research consortium BrainGate , contained a “Utah” array, a cluster of 100 spiky electrodes that is surgically embedded into the brain. In 2006, Matthew Nagle, a man with spinal cord paralysis, received a brain implant that allowed him to control a computer cursor.

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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. Understanding Word2Vec Word2Vec is a pioneering natural language processing (NLP) technique that revolutionized the way we represent words in vector space.

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Cambridge Intelligence

NOVEMBER 8, 2023

Earthquake data as a geospatial visualization A map view reveals what we’d expect, that the largest clusters of earthquakes occur where tectonic plates meet. Additional investigation reveals that this was the 2013 Russian Okhotsk Sea earthquake. Let’s focus on the major earthquakes between 2010-2011, including the 9.1

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Clustering Data Visualization Database Data Models 64

Explosion

FEBRUARY 18, 2015

Part-of-speech Tagger In 2013, I wrote a blog post describing how to write a good part of speech tagger. The tutorial also recommends the use of Brown cluster features, and case normalization features, as these make the model more robust and domain independent. spaCy’s tagger makes heavy use of these features.

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Google Research AI blog

DECEMBER 8, 2022

A group of photons initially clustered on neighboring sites will evolve into a superposition of all possible paths each photon might have taken. Among all the possible configuration paths, the only possible scenario that survives is the configuration in which all photons remain clustered together in a bound state.

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phData

NOVEMBER 8, 2024

Partitioning and clustering features inherent to OTFs allow data to be stored in a manner that enhances query performance. 2013 - Apache Parquet and ORC These columnar storage formats were developed to optimize storage and speed within distributed storage and computing environments.

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Data Lakes Data Warehouse Database Azure 52

PyImageSearch

OCTOBER 2, 2023

VAEs were introduced in 2013 by Diederik et al. By visualizing this space, colored by clothing type, as shown in Figure 9 , we can discern clusters, patterns, and potential correlations between different attributes. Similar class labels tend to form clusters, as observed with the Convolutional Autoencoder.

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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., 2013; Goodfellow et al., 2012; Otsu, 1979; Long et al., Challenges in representation learning: A report on three machine learning contests. Neural Networks, 64, 59–63.

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Explosion

FEBRUARY 28, 2017

For the similarity metric, I’ve been using a distance function taken from Chen (2013) , which he terms Cauchy Similarity : def ChenCauchy(length): '''Create a trainable similarity function, that will return the similarity and a callback to compute the backward pass given the gradient.

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DrivenData Labs

DECEMBER 7, 2023

Solvers submitted a wide range of methodologies to this end, including using open-source and third party LLMs (GPT, LLaMA), clustering (DBSCAN, K-Means), dimensionality reduction (PCA), topic modeling (LDA, BERT), sentence transformers, semantic search, named entity recognition, and more. and DistilBERT.

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Natural Language Processing Clustering Data Science Data Analysis 130

ML Review

MARCH 5, 2019

Well, actually, you’ll still have to wonder because right now it’s just k-mean cluster colour, but in the future you won’t). Within both embedding pages, the user can choose the number of embeddings to show, how many k-mean clusters to split these into, as well as which embedding type to show. References Harris, Z. Mikolov, T.,

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Tableau

DECEMBER 1, 2021

IPO in 2013. Tableau had its IPO at the NYSE with the ticker DATA in 2013. Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. Gestalt properties including clusters are salient on scatters. March 2013), which is our cloud product. Release v1.0

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Tableau

DECEMBER 1, 2021

IPO in 2013. Tableau had its IPO at the NYSE with the ticker DATA in 2013. Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. Gestalt properties including clusters are salient on scatters. March 2013), which is our cloud product. Release v1.0

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Flipboard

NOVEMBER 24, 2023

Since joining SnapLogic in 2010, Greg has helped design and implement several key platform features including cluster processing, big data processing, the cloud architecture, and machine learning. Greg has published research in the areas of operating systems, parallel computing, and distributed systems.

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