CIO Business Intelligence

AUGUST 11, 2024

En 2013, la compañía inició un proceso de cambio tecnológico que afectó a todos sus sistemas con el objetivo de crear un ecosistema core fuerte y muy robusto, con unos procesos muy eficientes, que les permitiera crecer y escalar con todas las tecnologías que pudieran llegar en un futuro.

Machine Learning 113

Machine Learning Marketing Digital Transformation IT 113

Cloudera

JANUARY 7, 2021

However, collecting annotations for your use case is typically one of the most costly parts of the machine learning life cycle. These emerging categories may not contain enough examples for a traditional machine learning algorithm to learn from, making high-quality classification difficult or prohibitive. .

Machine Learning 107

Machine Learning Deep Learning IT 107

Smart Data Collective

JANUARY 26, 2021

We covered the benefits of using machine learning and other big data tools in translations in the past. Even by 2013, 90% of the data in the world had been generated within the previous two years. Big data technology has been instrumental in helping organizations translate between different languages. That’s just staggering.

Data Architecture 141

Data Architecture Big Data Data Strategy Data-driven 141

Sisense

MAY 26, 2020

As both words are semantically close to each other, machine learning models can easily understand that “delicious” also refers to the pasta tasting good. Word embedding is a type of word representation that allows words with similar meanings to be understood by machine learning algorithms.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

Data Science 101

APRIL 12, 2019

Dataiku is a top-rated computer software company that was founded in 2013 and its headquarters can be found in New York. This shows that the vast majority of the employees are satisfied with the company and they are also a top choice for data science and machine learning positions based on annual pay packages. 2 StreamSets.

Statistics 110

Statistics Data Science Machine Learning Software 110

Dataiku

MARCH 10, 2020

That’s why since Dataiku was founded in 2013, we’ve been focused not only on creating a best-in-class data science and machine learning platform for democratizing AI via collaboration, but also on creating a world-class team that builds, supports, and promotes Dataiku and its customers.

Machine Learning 13

Machine Learning Data Science IT 13

Smart Data Collective

JUNE 18, 2021

Machine learning technology has been instrumental to the future of the criminal justice system. Fortunately, machine learning and predictive analytics technology can also help on the other side of the equation. We have previously talked about the role of predictive analytics in helping solve crimes.

Predictive Analytics 93

Predictive Analytics Forecasting Analytics Big Data 93

CIO Business Intelligence

FEBRUARY 10, 2023

Randich, who came to FINRA.org in 2013 after stints as co-CIO of Citigroup and former CIO of Nasdaq, is no stranger to the public cloud. “We spent about a year and a half going through several bottlenecks, taking them out one at a time with Amazon engineers. And now we’re in a good place,” he says.

Unstructured Data 105

Unstructured Data Data Lake Machine Learning Enterprise 105

Dataiku

NOVEMBER 10, 2021

Founded in 2013 and built upon the mission of democratizing AI, Dataiku strives to bring advanced AI applications and machine learning technology to all enterprises in an efficient and reliable fashion.

Machine Learning 59

Machine Learning Enterprise Technology 59

AWS Big Data

DECEMBER 17, 2024

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. Amazon Redshift made significant strides in 2024, rolling out over 100 features and enhancements.

Data Lake 81

Data Lake Data Warehouse Data-driven Optimization 81

CIO Business Intelligence

AUGUST 12, 2022

With its business rapidly growing and customer expectations rising, Thermo Fisher Scientific is turning to machine learning and robotic process automation (RPA) to transform the customer experience. in 2013, Alfa Aesar in 2015, Affymetrix and FEI Co. in 2016, and BD Advanced Bioprocessing in 2018.

IT 105

IT Data Lake Sales Machine Learning 105

CIO Business Intelligence

JULY 27, 2022

His endeavour to get into the technology space led him to learn about enterprise application platforms and he eventually started his ERP career at IBM. Since 2013 he’s been overseeing the Dangote Group’s IT operations across Africa. . Artificial Intelligence, Cloud Management, Machine Learning, Manufacturing Industry

Manufacturing 98

Manufacturing Machine Learning Technology Management 98

Smart Data Collective

JULY 11, 2019

New machine learning tools improve the design process, which makes customers have a better experience. In 2013, Bookmark became one of the first companies to use machine learning to improve web design. They must invest in the right machine learning and big data technology to get the most from their investments.

Big Data 90

Big Data Machine Learning Marketing Interactive 90

AWS Big Data

JULY 11, 2024

ProtT5-XL-UniRef50 is a machine learning (ML) model specifically designed to understand the language of proteins by converting protein sequences into multidimensional embeddings. ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning”. IEEE Trans Pattern Anal Mach Intell. Mikolov, T.;

Machine Learning 96

Machine Learning Modeling Data Processing Testing 96

AWS Big Data

MARCH 13, 2024

RAG is a machine learning (ML) architecture that uses external documents (like Wikipedia) to augment its knowledge and achieve state-of-the-art results on knowledge-intensive tasks. He entered the big data space in 2013 and continues to explore that area. This is where the Retrieval Augmented Generation (RAG) technique comes in.

Data Processing 123

Data Processing Dashboards Machine Learning Metrics 123

CIO Business Intelligence

JUNE 24, 2024

Machine learning requires fewer resources, while deep learning and generative AI require massive environments due to their complexity. Taking an energy-efficient facility that we built in 2013, we were able to meet their demanding requirements for high-power density and connectivity with minimal changes to our facility.

Strategy 111

Strategy Machine Learning Technology Deep Learning 111

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 112

Data Warehouse Analytics Data Lake Machine Learning 112

Dataiku

MARCH 4, 2021

Since our founding in 2013 and through the growth of the market and of Dataiku itself, we’ve delivered on our vision to connect thousands of people across organizations, unifying our customers’ approach to and ability to execute on data science, machine learning, and AI projects at scale.

Machine Learning 45

Machine Learning Enterprise Data Science Marketing 45

IBM Big Data Hub

FEBRUARY 29, 2024

Containers and Docker Container technology fundamentally changed in 2013 with Docker’s introduction and has continued unabated into this decade, steadily gaining in popularity and user acceptance. Docker containers were originally built around the Docker Engine in 2013 and run according to an application programming interface (API).

Data Processing 82

Data Processing Software Marketing Optimization 82

AWS Big Data

AUGUST 7, 2023

Amazon Redshift ML makes it easy for data analysts and database developers to create, train, and apply machine learning (ML) models using familiar SQL commands in Amazon Redshift. With Redshift ML, you can take advantage of Amazon SageMaker , a fully managed ML service, without learning new tools or languages.

Forecasting 90

Forecasting Data Warehouse Machine Learning Modeling 90

Domino Data Lab

DECEMBER 1, 2019

In the context of machine learning, we consider data drift 1 to be the change in model input data that leads to a degradation of model performance. A Survey on Concept Drift Adaptation” ACM Computing Survey Volume 1 , Article 1 (January 2013). LeCun, Yann; Corinna Cortes; Christopher J.C.

Machine Learning 77

Machine Learning Modeling Deep Learning Testing 77

bridgei2i

JULY 28, 2020

It is my immense pleasure to introduce you all to our guest today Ria Persad, she’s named as international woman of the year by Renewable Energy World in power engineering in 2013 and the lifetime achievement leader by Platts Global Energy awards in 2014. More efficient, more scalable systems are going to be able to handle more data.

Enterprise 98

Enterprise Digital Transformation Insurance B2B 98

CIO Business Intelligence

DECEMBER 13, 2024

Como CIO de Bosch en Espaa desde 2013 y miembro del Comit de Direccin de Robert Bosch Iberia, reporto directamente al presidente. Con una presencia arraigada en Espaa desde hace ms de 100 aos, Bosch contina impulsando la transformacin digital en el pas, mejorando la eficiencia y la competitividad en sectores diversos de la mano de Relao.

IoT 97

IoT B2B Machine Learning IT 97

Timo Elliott

JANUARY 10, 2022

Here in Europe, we have agreed to a 55% reduction in emissions by 2013, which is incredibly ambitious, and I think a lot of people don’t realize the kind of level of systemic change that will require. They are applying machine learning to create more intelligent trade claims management. Live and learn.

Data Processing 122

Data Processing Machine Learning Manufacturing Technology 122

Howard Dresner

FEBRUARY 11, 2014

Collaboration BI At one of my weekly #BIWisdom tweetchats this month, collaboration, social media and text analytics turned up in a discussion about 2013 BI predictions that didn’t pan out. It was keyboard based and turned up a lot of false positives.” • “This needs more machine learning algorithms than most tools use today.

Analytics 45

Analytics Business Intelligence Data Processing Machine Learning 45

AWS Big Data

NOVEMBER 14, 2023

Wallapop’s initial data architecture platform Wallapop is a Spanish ecommerce marketplace company focused on second-hand items, founded in 2013. Since its creation in 2013, it has reached more than 40 million downloads and more than 700 million products have been listed. The marketplace can be accessed via mobile app or website.

Data Warehouse 64

Data Warehouse Analytics Testing Cost-Benefit 64

CIO Business Intelligence

AUGUST 1, 2024

After a data breach in 2013 , Target made substantial investments in cybersecurity. Addressing technical debt is essential for maintaining a strong security posture and ensuring the long-term resilience of the organization against sophisticated cyberthreats.

Cost-Benefit 98

Cost-Benefit Measurement Data-driven Marketing 98

DataRobot

OCTOBER 27, 2021

Between 2013 and 2017, job listings in 27 states rose by 11 percent while applicant numbers tumbled by 24 percent, compounding talent vacancy issues within state and local governments. Machine learning models are transparent and explainable and consider only business-relevant information to avoid bias and promote equity and fairness.

Machine Learning 52

Machine Learning Modeling Reporting IT 52

Domino Data Lab

JANUARY 6, 2019

I’ve been teaching data science since 2008 privately for employers – exec staff, investors, IT teams, and the data teams I’ve led – and since 2013, for industry professionals in general. If you live on the furthermost edges of rural Newfoundland (as some of my relatives do), then remote learning via MOOCs is probably a good option.

Data Science 56

Data Science Machine Learning Visualization Reporting 56

Cloudera

AUGUST 6, 2018

For example, Crisis Text Line , which provides online support to people in crisis, received a total of 8 m illion text messages in the first two years of its existence between 2013 and 2015. There are legitimate concerns about the inherent biases of machine learning algorithms.

Machine Learning 50

Machine Learning Internet of Things Data-driven Cost-Benefit 50

Ontotext

FEBRUARY 6, 2020

After obtaining information from images and videos, computer vision systems use machine learning methods to train computers to process and analyze patterns across faces. The solution is based on the computer vision technology that has been developed within Sirma Group since 2013 and now complements Ontotext’s portfolio within Sirma AI.

Technology 52

Technology Machine Learning Visualization Publishing 52

Domino Data Lab

APRIL 21, 2021

In this article, we’ll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human eye might not catch. Credit card fraud represents a significant problem for financial institutions, and reliable fraud detection is generally challenging.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

CIO Business Intelligence

JUNE 28, 2023

Many CIOs have become the de facto generative AI professor and spent ample time developing 101 materials and conducting roadshows to build awareness, explain how generative AI differs from machine learning, and discuss the inherent risks. According to Ronanki, they aspired to replace human doctors with machines in diagnosing cancer.

Enterprise 52

Enterprise Experimentation Risk Data-driven 52

Sisense

DECEMBER 11, 2019

Kongregate has been using Periscope Data since 2013. Kyle said: We empower data analysts to create more business value than any other BI platform. Kyle Dempsey, Senior Sales Engineer, Sisense.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

Sisense

JUNE 26, 2020

Machine learning and advanced analytics are helping humans make sense of large amounts of structured and unstructured data by leaning into our natural ability to make a better sense of visuals than the raw data we want to understand. The good news is, you don’t have to!

Visualization 97

Visualization Unstructured Data Measurement Data-driven 97

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

by OMKAR MURALIDHARAN Many machine learning applications have some kind of regression at their core, so understanding large-scale regression systems is important. But most common machine learning methods don’t give posteriors, and many don’t have explicit probability models. For more on ad CTR estimation, refer to [2].

KDD 40

KDD Testing Machine Learning Measurement 40

BizAcuity

MAY 10, 2022

2013: Google launches Google Compute Engine (IaaS), its own version of EC2. Microsoft launches Azure ML Studio for machine learning capabilities on the cloud. AWS rolls out SageMaker, designed to build, train, test and deploy machine learning (ML) models. FaaS comes as a breakthrough for serverless computing.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52