Cloudera

FEBRUARY 16, 2018

In many ways, 2017 was a singular year for Cloudera, not least because we staged a successful IPO and joined the ranks of the world’s fastest-growing, publicly traded companies. UK’s V3 Technology Award as best AI/Machine Learning Provider. The post 2017 – Another Award-Winning Year for Cloudera!

IoT 45

IoT Machine Learning Manufacturing Data Science 45

Smart Data Collective

JULY 28, 2022

The financial industry is becoming more dependent on machine learning technology with each passing day. Machine learning has helped reduce man-hours, increase accuracy and minimize human bias. The good news is that predictive analytics technology can reduce risk exposure for these investors.

Predictive Analytics 136

Predictive Analytics Analytics Forecasting Machine Learning 136

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. Why aren’t traditional software tools sufficient?

Modeling 193

Modeling Machine Learning Testing Metrics 193

O'Reilly on Data

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Up until 2017, the ML+AI topic had been amongst the fastest growing topics on the platform. Coincidence? Probably not, but only time will tell. to be wary of.

Data-driven 331

Data-driven Software Statistics Marketing 331

CIO Business Intelligence

JANUARY 4, 2023

billion in stock buybacks between 2017 and 2019. In 2017, Fast Company wrote that Southwest Airlines’ digital transformation “takes off” with an $800 million technology overhaul, but only $300 million was dedicated to new technology for operations. 31 what amounts to $428 million a year.

Digital Transformation 135

Digital Transformation Software Technology Modeling 135

CIO Business Intelligence

APRIL 15, 2022

In 2017, The Economist declared that data, rather than oil, had become the world’s most valuable resource. And 20% of IT leaders say machine learning/artificial intelligence will drive the most IT investment. The algorithm learned to identify children, not high-risk patients.

Analytics 144

Analytics Machine Learning Insurance Testing 144

CIO Business Intelligence

DECEMBER 7, 2023

In 2017, the university created its Education and Research Center for Disaster Risk Reduction and Redesign that focuses on disaster relief – including disaster medicine, prevention education, and reconstruction design. So far, the solution has increased details about disaster-response risk by 40% over traditional methods.

IoT 82

IoT Internet of Things Forecasting Digital Transformation 82

Data Science 101

APRIL 26, 2019

Gopher Data – Gophers doing data analysis, no schedule events, last blog post was 2017 Gopher Notes – Golang in Jupyter Notebooks Lgo – Interactive programming with Jupyter for Golang Gota – Data frames for Go, “The API is still in flux so use at your own risk.” Machine Learning with Go?

Data Science 111

Data Science Machine Learning Interactive Risk 111

Cloudera

NOVEMBER 1, 2022

A quick trip in the congressional time machine to revisit 2017’s Modernizing Government Technology Act surfaces some of the most salient points regarding agencies’ challenges: The federal government spends nearly 75% of its annual information technology funding on operating and maintaining existing legacy information technology systems.

Cost-Benefit 87

Cost-Benefit Data Architecture Risk IoT 87

CIO Business Intelligence

MARCH 25, 2022

Two years of pandemic uncertainty and escalating business risk have sharpened the focus of corporate boards on a technology trend once dismissed as just another IT buzzword. I bring the tech and cyber expertise to those boards, and also the digital piece,” adds Martin, a member of the CIO Hall of Fame since 2017. “It

Digital Transformation 100

Digital Transformation Uncertainty Machine Learning Strategy 100

Domino Data Lab

MAY 8, 2019

I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

CIO Business Intelligence

SEPTEMBER 7, 2022

Dubbed Cropin Cloud, the suite comes with the ability to ingest and process data, run machine learning models for quick analysis and decision making, and several applications specific to the industry’s needs. The company says it has partnered with more than 250 B2B customers.

B2B 86

B2B Contextual Data IoT Deep Learning 86

Smart Data Collective

JULY 17, 2019

In 2017, the number of seniors over the age of 65 reached a record 1 billion people. Companies that strive to provide better senior care can use machine learning, robotics and predictive analytics to better meet the needs of their residents without having to worry about a frustrating staffing shortage. Cutting marketing costs.

Cost-Benefit 83

Cost-Benefit Machine Learning Advertising IoT 83

Cloudera

MAY 15, 2018

Cloudera Enterprise is the market leader in this space and working closely with the wider open source community to integrate the latest innovations in machine learning and artificial intelligence (AI). Derman (2016), Cesa (2017) & Bouchard (2018)). Probability, Uncertainty and Quantitative Risk (2017) 2:6.

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

Cloudera

SEPTEMBER 10, 2021

By more effectively leveraging its petabytes of current and historical data, the IRS is working to stave off costly fraud and waste, more efficiently deliver on fundamental missions, and better protect taxpayers, including from risks such as identity theft.

Machine Learning 67

Machine Learning Statistics Data-driven Big Data 67

Smart Data Collective

FEBRUARY 14, 2023

It’s seemingly compulsory for most developers to build mobile versions of their applications or risk losing millions of potential users. This includes utilizing personalization technology, which relies heavily on machine learning. Many people tend to forget their app updates, which can pose significant risks.

Risk 115

Risk Technology Optimization Machine Learning 115

IBM Big Data Hub

AUGUST 1, 2023

We are bringing the power of foundation models with the availability of a GPU as a service on IBM Cloud offering to help organizations tap into artificial intelligence (AI) in a secured environment while aiming to mitigate third- and fourth-party risk.

Digital Transformation 64

Digital Transformation Risk Data Processing Enterprise 64

datapine

NOVEMBER 27, 2019

This is one of the major trends chosen by Gartner in their 2020 Strategic Technology Trends report , combining AI with autonomous things and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. The fact is that it is and will affect our lives, whether we like it or not.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Cloudera

MARCH 3, 2022

In 2017, Anthem reported a data breach that exposed thousands of its Medicare members. Data analytics and machine learning can become a business and a compliance risk if data security, governance, lineage, metadata management, and automation are not holistically applied across the entire data lifecycle and all environments.

Data Governance 98

Data Governance Enterprise Data Quality Metadata 98

Jen Stirrup

FEBRUARY 1, 2023

The effects of AI will be magnified in the coming decade as manufacturing, retailing, transportation, finance, health care, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning.

Recreation/Entertainment 63

Recreation/Entertainment Testing Advertising Insurance 63

CIO Business Intelligence

MAY 20, 2022

That’s what some people asked of Adriana “Andi” Karaboutis, the former CIO of Dell who left the computer giant and was named National Grid’s global chief information and digital officer in 2017. Optimizing with machine learning. Her answer? She gets to change the world.

IT 95

IT Digital Transformation Internet of Things Data Architecture 95

CIO Business Intelligence

JUNE 28, 2023

So the longer somebody is left at the side of the road, the higher the risk is for that individual. So in 2017, Kin along with CEO Jay Woo devised an idea to create a machine learning system that helps predict where the next incident is going to happen. Artificial Intelligence, CIO, IT Leadership, Machine Learning

Machine Learning 52

Machine Learning Insurance Technology Interactive 52

O'Reilly on Data

JANUARY 25, 2021

We’re not pretending the frameworks themselves are comparable—Spring is primarily for backend and middleware development (though it includes a web framework); React and Angular are for frontend development; and scikit-learn and PyTorch are machine learning libraries. Observability” risks becoming the new name for monitoring.

Machine Learning 362

Machine Learning Software Testing Technology 362

Domino Data Lab

JULY 2, 2019

Doesn’t this seem like a worthy goal for machine learning—to make the machines learn to work more effectively? For more background about program synthesis, check out “ Program Synthesis Explained ” by James Bornholt from 2015, as well as the more recent “ Program Synthesis in 2017-18 ” by Alex Polozov from 2018.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Domino Data Lab

MAY 20, 2021

Machine Learning algorithms often need to handle highly-imbalanced datasets. This carries the risk of this modification performing worse than simpler approaches like majority under-sampling. note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017).

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Cloudera

MAY 10, 2018

Cloudera 2017 Data Impact Award Winners. With advancements in exploratory data science, machine learning, predictive analytics, AI, and data engineering, the world is increasingly driven by data. Enterprise machine learning. Nominate a project or learn more about the program here. Read how to get nominated.

Machine Learning 41

Machine Learning Predictive Analytics Data-driven Data Science 41

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Interpretable Machine Learning , Christoph Molnar, Section 5.1,

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Cloudera

MAY 27, 2021

This could be addressed with an explanation of how a technology works — how, for instance, machine learning (ML) engines get better at their tasks by being fed gobs of data. Sometimes, even if everything is done to deliver ethical outcomes, the machine may still make predictions and assumptions that don’t abide by these rules.

Machine Learning 117

Machine Learning Big Data Consulting Technology 117

IBM Big Data Hub

MAY 26, 2023

In 2017, 94% of hospitals used electronic clinical data from their EHR. With the growth in usage of digital technology and cloud in the life sciences industry, digital information is more readily available and at a greater risk for exploitation. Given the rise of AI, ChatGPT and Web3.0, million.

Consulting 74

Consulting Cost-Benefit Optimization Machine Learning 74

CIO Business Intelligence

APRIL 24, 2023

How we got here The most notable enabling technologies in generative AI are deep learning, embeddings, transfer learning (all of which emerged in the early to mid-2000s), and neural net transformers (invented in 2017). Deep learning emerged in academia in the early 2000s, with broader industry adoption starting around 2010.

Enterprise 52

Enterprise Deep Learning Modeling Machine Learning 52

IBM Big Data Hub

JULY 19, 2023

The explosion in digital data—in combination with declining availability of skilled and willing human resources to ingest and process the digital data in a compliant manner—is forcing life sciences organizations to explore AI, machine learning and now generative AI technologies. Why IBM Consulting for generative AI on AWS?

Consulting 60

Consulting Machine Learning Manufacturing Optimization 60

BizAcuity

APRIL 28, 2019

is delinquent as of June 30th, 2017. Today, it’s no secret that most forward-thinking businesses are keenly following the latest developments on big data, artificial intelligence, machine learning, and predictive analytics. Their issue at hand was to decrease the Portfolio at Risk.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

Smart Data Collective

JULY 8, 2019

between 2016 and 2017. Companies around the world are facing rising risks of accidents. New predictive analytics and machine learning technology should address these concerns. Accident data provides insight and valuable information that can be used to help improve safety in the future. increased by 5.3%

Big Data 77

Big Data Measurement Reporting Predictive Analytics 77

Jen Stirrup

OCTOBER 3, 2019

The future is likely to be even more defined by the technology that is currently evolving – and if companies neglect to take a practical, thoughtful and responsible approach to implementing and developing this software, they run the risk of not being able to catch up with the consequences. . Miller, Wolf and Grodzinsky, 2017).

Technology 40

Technology Machine Learning Interactive Risk 40

Jet Global

SEPTEMBER 4, 2020

When Microsoft released the next generation of the product in 2017, Microsoft Dynamics 365 for Finance and Supply Chain Management (D365F&SCM) , there were some significant changes behind the scenes. Data Entities. One very important change had to do with access to the database. Another Alternative to BYOD.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

O'Reilly on Data

JANUARY 22, 2019

They trade the markets using quantitative models based on non-financial theories such as information theory, data science, and machine learning. Yet, finance textbooks, programs, and professionals continue to use the normal distribution in their asset valuation and risk models because of its simplicity and analytical tractability.

Modeling 133

Modeling Finance Uncertainty Data mining 133

Alation

FEBRUARY 13, 2020

In The Forrester Wave: Machine Learning Data Catalogs, 36% to 38% of global data and analytics decision makers reported that their structured, semi-structured, and unstructured data each totaled 1,000 TB or more in 2017, up from only 10% to 14% in 2016.

ROI 52

ROI Cost-Benefit Unstructured Data Data Lake 52