Snorkel AI

MARCH 9, 2023

The project itself debuted in 2014, and has become the infrastructure backbone of many modern software companies and their products. Each k8s cluster is made up of two key components: the k8s control plane and an arbitrary number of attached worker nodes whose sole job is to run containers. Scaling down the cluster’s size.

ML 52

ML ML Clustering Data Scientist 52

Snorkel AI

MARCH 9, 2023

The project itself debuted in 2014, and has become the infrastructure backbone of many modern software companies and their products. Each k8s cluster is made up of two key components: the k8s control plane and an arbitrary number of attached worker nodes whose sole job is to run containers. Scaling down the cluster’s size.

ML 52

ML ML Clustering Data Scientist 52

Mlearning.ai

APRIL 1, 2023

Doc2Vec was introduced in 2014 by a team of researchers 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.

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Clustering 52

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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AI AI Artificial Intelligence Artificial Intelligence 181

AWS Machine Learning Blog

NOVEMBER 16, 2023

Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care. These environments ranged from individual laptops and desktops to diverse on-premises computational clusters and cloud-based infrastructure.

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Mlearning.ai

JUNE 8, 2023

Clustering  — we can cluster our sentences, useful for topic modeling. Doc2Vec: introduced in 2014, adds on to the Word2Vec model by introducing another ‘paragraph vector’. The article is clustering “Fine Food Reviews” dataset. Enables search to be performed on concepts (rather than specific words).

Machine Learning 52

Machine Learning Machine Learning Clustering Database 52

DagsHub

APRIL 7, 2024

The project was created in 2014 by Airbnb and has been developed by the Apache Software Foundation since 2016. Cloud-agnostic and can run on any Kubernetes cluster. Integration: It can work alongside other workflow orchestration tools (Airflow cluster or AWS SageMaker Pipelines, etc.)

Machine Learning 59

Machine Learning Machine Learning ML ML 59

phData

MARCH 29, 2024

Founded in 2014 by three leading cloud engineers, phData focuses on solving real-world data engineering, operations, and advanced analytics problems with the best cloud platforms and products. Over the years, one of our primary focuses became Snowflake and migrating customers to this leading cloud data platform.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Cambridge Intelligence

JUNE 28, 2023

It’s a busy chart, but I’m drawn to the cluster of larger team nodes in the top left. In 2014, London also hosted the finish of a stage that started in my hometown, Cambridge. Visualizing the Tour de France: the early years Hmmmm. Those “TDF 190# ” don’t look right – they’re clearly not teams – but I know what’s happened.

Clustering 52

Clustering Data Visualization 52

AWS Machine Learning Blog

MAY 7, 2024

Founded in 2014, Veritone empowers people with AI-powered software and solutions for various applications, including media processing, analytics, advertising, and more. Search index creation We use an OpenSearch cluster (OpenSearch Service domain) with t3.medium.search

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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., 2012; Otsu, 1979; Long et al., 2013; Goodfellow et al., Contour detection and hierarchical image segmentation. Goodfellow, I. Shlens, J., & Szegedy, C. Goodfellow, I.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

MAY 16, 2023

Skilled in programming languages such as Python, R, and SQL, and have worked on various projects involving predictive modeling, clustering, and classification. Passionate about leveraging data to drive business decisions and improve customer experience.

Data Scientist 52

Data Scientist Data Science SQL Python 52

Cambridge Intelligence

OCTOBER 19, 2023

” First release: 2014 (of Cosmos DB itself) Format: A commercial, hosted, multi-model database with a property graph database service via the Gremlin API Top 3 advantages: A Microsoft Azure service – as part of the Azure family, Cosmos DB’s graph capability comes with SLA-backed speed and throughput, access, and 99.999% availability.

Database 59

Database Azure SQL Analytics 59

Explosion

MAY 17, 2023

In 2014 I started working on spaCy , and here’s an excerpt of how I explained the motivation for the library: Computers don’t understand text. We all spend a big part of our working lives writing, reading, speaking and listening. This is unfortunate, because that’s what the web almost entirely consists of.

Supervised Learning 135

Supervised Learning Natural Language Processing Clustering Machine Learning 135

Explosion

FEBRUARY 18, 2015

This is easy to do, as spaCy loads a vector-space representation for every word (by default, the vectors produced by Levy and Goldberg (2014) _). The only problem is that the list really contains two clusters of words: one associated with the legal meaning of “pleaded”, and one for the more general sense.

Clustering 52

Clustering Natural Language Processing Machine Learning Machine Learning 52

AWS Machine Learning Blog

JANUARY 13, 2023

They were admitted to one of 335 units at 208 hospitals located throughout the US between 2014–2015. Finally, monitor and track the FL model training progression across different nodes in the cluster using the weights and biases (wandb) tool, as shown in the following screenshot.

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AWS Analytics Analytics Machine Learning 97

Explosion

FEBRUARY 18, 2015

The tutorial also recommends the use of Brown cluster features, and case normalization features, as these make the model more robust and domain independent. Dependency Parser The parser uses the algorithm described in my 2014 blog post. The following tweaks: I use Brown cluster features — these help a lot; I redesigned the feature set.

Algorithm 40

Algorithm Python Clustering 40

PyImageSearch

OCTOBER 2, 2023

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. The torch.nn Auto-Encoding Variational Bayes.

Deep Learning 108

Deep Learning Deep Learning Clustering Computer Science 108

Mlearning.ai

FEBRUARY 28, 2023

Year: More than half the cars in the data were manufactured in or after 2014. The next step post that would be to cluster different sets of data and see if multiple models should be created for different locations and car types. The log transformation was applied on this column to reduce skewness. I hope you enjoyed this post.

Python 52

Python EDA Exploratory Data Analysis Data Analysis 52

DagsHub

OCTOBER 23, 2024

Apache Hadoop Apache Hadoop is an open-source framework that supports the distributed processing of large datasets across clusters of computers. BLEU on the WMT 2014 English- to-German translation task, improving over the existing best results, including ensembles, by over 2 BLEU. Our model achieves 28.4 after training for 3.5

Machine Learning 52

Machine Learning Machine Learning AI AI 52

ODSC - Open Data Science

JANUARY 29, 2024

These outputs, stored in vector databases like Weaviate, allow Prompt Enginers to directly access these embeddings for tasks like semantic search, similarity analysis, or clustering. GANs, introduced in 2014 paved the way for GenAI with models like Pix2pix and DiscoGAN.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52

Hacker News

JANUARY 9, 2024

The LLMs Have Landed The machine learning superfunctions Classify and Predict first appeared in Wolfram Language in 2014 ( Version 10 ). but with things like clustering). Spreading the power of the Wolfram Language to more and more people and areas.

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Python Algorithm Machine Learning Machine Learning 181

AWS Machine Learning Blog

APRIL 5, 2024

Among these models, the spatial fixed effect model yielded the highest mean R-squared value, particularly for the timeframe spanning 2014 to 2020. SageMaker Processing enables the flexible scaling of compute clusters to accommodate tasks of varying sizes, from processing a single city block to managing planetary-scale workloads.

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Clustering ML ML AWS 136

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.

AI 40

AI AI Clustering Machine Learning 40

phData

NOVEMBER 9, 2023

If you go back to 2014, data warehouse platforms were built using legacy architectures that had drawbacks when it came to cost, scale, and flexibility. Effectively this is a way to store the source of truth and build (or rebuild) your downstream data products (including data warehouses) from it. Historically, there were big differences.

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Data Warehouse Data Lakes Clustering Cloud Data 98

DrivenData Labs

DECEMBER 11, 2024

Looking back ¶ When we started DrivenData in 2014, the application of data science for social good was in its infancy. The startup cost is now lower to deploy everything from a GPU-enabled virtual machine for a one-off experiment to a scalable cluster for real-time model execution.

Data Science 148

Data Science Data Scientist Machine Learning Machine Learning 148

Tableau

DECEMBER 1, 2021

Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. June 2014) to give people who understand joins a better experience than a dialog. Gestalt properties including clusters are salient on scatters. Let’s take a look at each. . Query innovation. Connectivity.

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AWS Machine Learning Blog

JANUARY 26, 2023

Since March 2014, Best Egg has delivered $22 billion in consumer personal loans with strong credit performance, welcomed almost 637,000 members to the recently launched Best Egg Financial Health platform, and empowered over 180,000 cardmembers who carry the new Best Egg Credit Card in their wallet.

ML 100

ML ML Data Scientist AWS 100

Tableau

DECEMBER 1, 2021

Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. June 2014) to give people who understand joins a better experience than a dialog. Gestalt properties including clusters are salient on scatters. Let’s take a look at each. . Query innovation. Connectivity.

Tableau 98

Tableau ML ML Database 98

AWS Machine Learning Blog

MAY 24, 2023

Batch transform is cost-effective because unlike real-time hosted endpoints that have persistent hardware, batch transform clusters are torn down when the job is complete and therefore the hardware is only used for the duration of the batch job.

Machine Learning 96

Machine Learning Machine Learning Natural Language Processing ML 96