CIO

OCTOBER 1, 2022

Cretella says P&G will make manufacturing smarter by enabling scalable predictive quality, predictive maintenance, controlled release, touchless operations, and manufacturing sustainability optimization. These things have not been done at this scale in the manufacturing space to date, he says. Smart manufacturing at scale.

Artificial Inteligence 361

Artificial Inteligence Azure IoT Analytics 361

Xebia

FEBRUARY 25, 2024

This post is based on a tutorial given at EuroPython 2023 in Prague: How to MLOps: Experiment tracking & deployment and a Code Breakfast given at Xebia Data together with Jeroen Overschie. Machine learning operations: what and why MLOps, what the fuzz? MLOps stands for machine learning (ML) operations.

Applications 130

Applications Technical Review Software Review Azure 130

O'Reilly Media - Ideas

JANUARY 8, 2019

In a recent O’Reilly survey , we found that the skills gap remains one of the key challenges holding back the adoption of machine learning. The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. Continuing investments in (emerging) data technologies. Burgeoning IoT technologies.

Trends 87

Trends Data Machine Learning Artificial Inteligence 87

OTS Solutions

MARCH 14, 2019

They have started pilot projects that are associated with machine learning algorithms and their role in improving certain aspects of their business such as customer relationships and cyber security. This investment in AI technology is expected to continue. Include Responsibility and Accountability. Practice Participatory Design.

Artificial Inteligence 140

Artificial Inteligence Artificial Intelligence Strategy Technical Review 140

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Deep Learning.

Big Data 85

Big Data Technology Tools Cloud 85

Cloudera

FEBRUARY 1, 2024

The other half of the equation requires your team’s emphasis to shift to sustained excellence in managing and optimizing your data ecosystem — better known as Day 2 operations. Moreover, it is a period of dynamic adaptation, where documentation and operational protocols will adapt as your data and technology landscape change.

Backup 82

Backup Architecture Cloud Resources 82

O'Reilly Media - Ideas

MARCH 19, 2020

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. What’s driving this growth? disproportionately involve Python.

Artificial Inteligence 113

Artificial Inteligence Trends Artificial Intelligence Machine Learning 113

ParkMyCloud

DECEMBER 11, 2020

As another free Google Cloud training option, Google has also teamed up with Coursera , an online learning platform founded by Stanford professors, to offer courses online so you can “skill up from anywhere.”. Here you’ll learn new skills in a GCP environment and earn cloud badges along the way. Plural Sight.

Google Cloud 97

Google Cloud Training Resources Cloud 97

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. It’s not the machine’s fault. A chatbot that now relies mostly on canned answers eventually becomes more precise and useful.

Artificial Inteligence 119

Artificial Inteligence Artificial Intelligence Technical Review Systems Review 119

O'Reilly Media - Ideas

AUGUST 26, 2019

Among the fastest-growing topics are those central to building AI applications: machine learning (up 58% from 2018), data science (up 53%), data engineering (up 58%), and AI itself (up 52%). Introduction to Machine Learning with Python: A Guide for Data Scientists.

Artificial Inteligence 39

Artificial Inteligence Organization Machine Learning Artificial Intelligence 39

CIO

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 319

Analytics Data Engineering Machine Learning Artificial Inteligence 319

Cloudera

APRIL 13, 2021

You’ve probably heard it more than once: Machine learning (ML) can take your digital transformation to another level. And while you’d be forgiven for thinking that it might sound too good to be true, operational ML is , in fact, achievable and sustainable. As mentioned in Step 7, models must be fed, sustained, and controlled.

Machine Learning 98

Machine Learning Artificial Inteligence Enterprise eBook 98

InfoQ Culture Methods

JANUARY 19, 2022

Topics explored included: hybrid working and the importance of ethics and sustainability within technology. In this podcast summary Thomas Betts, Wes Reisz, Shane Hastie, Charles Humble, Srini Penchikala, and Daniel Bryant discuss what they have seen in 2021 and speculate a little on what they hope to see in 2022.

Technical Review 99

Technical Review Sustainability Artificial Inteligence Technology 99

Capgemini

MARCH 16, 2023

Technological innovation within life sciences XOps is about the smooth delivery of technological innovations into sustainable and flexible production environments. We are working with various machine learning models, a graph database, a data pipeline step to ingest from other databases, and a lot of software with very specific UX needs.

Pharmaceuticals 52

Pharmaceuticals Innovation Machine Learning Artificial Inteligence 52

Cloudera

JANUARY 20, 2021

Predictive Analytics – predictive analytics based upon AI and machine learning (Fraud detection, predictive maintenance, demand based inventory optimization as examples). Security & Governance – an integrated set of security, management and governance technologies across the entire data lifecycle.

Data 110

Data Artificial Inteligence Analytics Machine Learning 110

Apiumhub

APRIL 5, 2022

With over 1000 practical case studies presented on the past 6 editions and with new geo events in the MEA and the APAC region, the event is a worldwide movement, ushering the community of data, analytics and AI practitioners across functions, companies, industries, sectors, countries and regions to collaborate, benchmark, share and innovate.

Innovation 52

Innovation Data Artificial Inteligence Case Study 52

Apiumhub

APRIL 1, 2021

Learning data science through books will help you get a holistic view of Data Science as data science is not just about computing, it also includes mathematics, probability, statistics, programming, machine learning, and much more. Top Data science books you should definitely read.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

Datavail

MARCH 31, 2022

However, they can also use their business modeling processes to develop sustained value creation over time, not just maintain the status quo. Today’s thriving companies are embracing emerging data analytics programs to upgrade their business modeling technology from systems maintenance to value creation. Contact us today.

Business Analytics 52

Business Analytics Analytics Artificial Inteligence Strategy 52

BPM

JANUARY 18, 2019

Leading analyst firms seem to return to the roots of BPM as an orchestration layer implemented by workflow automation, and at least from where we stand it looks like this is a rapidly growing, sustainable market. Those organizations that can figure out how to launch, execute, and sustain BIG CHANGE will the big winners in 2019.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Netflix Tech

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 40

AWS Open Source Linux Off-The-Shelf 40

Netflix Tech

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 40

AWS Open Source Linux Off-The-Shelf 40

TIBCO - Connected Intelligence

SEPTEMBER 29, 2021

“There was a lot of data sprawl, and as a data scientist, it was tough to access all the data from different sources.”. “We Having easier access to data has eliminated the need for basic data engineering, and now our data scientists can do analysis and business intelligence work instead.”.

Data 49

Data Artificial Inteligence Energy Artificial Intelligence 49

Coforge

AUGUST 31, 2020

The drastic shift from traditional and orthodox system frameworks and operations can be unarguably attributed to the influx of intelligent technologies such as Artificial Intelligence, Machine Learning, Big Data, Blockchain/DLT led smart contracts, and widespread usage of cloud systems. .

Insurance 40

Insurance Technology Artificial Inteligence Policies 40

InfoQ Culture Methods

JANUARY 13, 2023

2022 was another year of significant technological innovations and trends in the software industry and communities. The InfoQ podcast co-hosts met last month to discuss the major trends from 2022, and what to watch in 2023. This article is a summary of the 2022 software trends podcast.

Trends 113

Trends Software Report Innovation 113

Altexsoft

JUNE 6, 2019

Forecasting demand with machine learning in Walmart. Systems that rely on machine learning are capable of analyzing a multitude of data points, finding subtle patterns (indicating changes in customer preferences, behavior, or satisfaction) which can be non-obvious for a human. Source: Lenovo StoryHub.

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

Altexsoft

APRIL 13, 2023

You can read the details on them in the linked articles, but in short, data warehouses are mostly used to store structured data and enable business intelligence , while data lakes support all types of data and fuel big data analytics and machine learning. Data siloes. into the digital twin.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

NOVEMBER 9, 2021

Traditional statistical methods use mainly internal, historical data to predict trends within relatively stable markets. Meanwhile, machine learning (ML) techniques are capable of processing a wide range of both historical and current data from multiple external and internal sources. Extract data. Consolidate data.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

O'Reilly Media - Ideas

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. Within the data topic, however, ML+AI has gone from 22% of all usage to 26%. In aggregate, data engineering usage declined 8% in 2019.

Technical Review 138

Technical Review Microservices Data Engineering Architecture 138

Altexsoft

OCTOBER 3, 2019

Predictive analytics requires numerous statistical techniques, including data mining (detecting patterns in data) and machine learning. Organizations already use predictive analytics to optimize operations and learn how to improve the employee experience. Let’s explore several popular areas of its application.

Analytics 16

Analytics Company Off-The-Shelf How To 16

O'Reilly Media - Ideas

FEBRUARY 11, 2020

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. Adopting AI can help data quality.

Weak Development Team 126

Weak Development Team Data Technical Review Survey 126

O'Reilly Media - Ideas

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?

Government 80

Government Artificial Inteligence Machine Learning Testing 80

O'Reilly Media - Ideas

MARCH 2, 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. Within the data topic, however, ML+AI has gone from 22% of all usage to 26%. Key survey results: The C-suite is engaged with data quality.

Agile 21

Agile Artificial Inteligence Weak Development Team SCRUM 21

Netflix Tech

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 15

AWS Open Source Linux Engineering Management 15

Altexsoft

OCTOBER 23, 2019

The scope includes companies working with machine learning, fintech, biotech, cybersecurity, smart cities, voice recognition, and healthtech. Southern Data Science Conference 2020. The matters of deep learning basics, application of data analytics and data science with different frameworks and tools will be discussed.

Security 13

Security Artificial Inteligence Conference Data Center 13

Cloudera

AUGUST 20, 2021

The Cloudera Data Platform comprises a number of ‘data experiences’ each delivering a distinct analytical capability using one or more purposely-built Apache open source projects such as Apache Spark for Data Engineering and Apache HBase for Operational Database workloads.

Strategy 98

Strategy Data Technical Review Weak Development Team 98

Cloudera

OCTOBER 25, 2022

Enabling data and analytics in the cloud allows you to have infinite scale and unlimited possibilities to gain faster insights and make better decisions with data. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Cloud 52

Cloud Data Firewall AWS 52

Daniel Bryant

SEPTEMBER 13, 2019

What was worth noting was that (anecdotally) even engineers from large organisations were not looking for full workload portability (i.e. There were also two patterns of adoption of HashiCorp tooling I observed from engineers that I chatted to: Infrastructure-driven?—?in

Infrastructure 8

Infrastructure Azure Software Engineering Cloud 8