CIO

APRIL 1, 2025

Job titles like data engineer, machine learning engineer, and AI product manager have supplanted traditional software developers near the top of the heap as companies rush to adopt AI and cybersecurity professionals remain in high demand.

Marketing 152

Marketing Software Development Software Development 152

CIO

SEPTEMBER 12, 2022

What our team has produced in the last few years is keeping in mind how to make people’s lives simpler and reducing commute times.”. Data engine on wheels’. To mine more data out of a dated infrastructure, Fazal first had to modernize NJ Transit’s stack from the ground up to be geared for business benefit. “I

Data Engineering 174

Data Engineering Engineering Data Transportation 174

InfoQ Culture Methods

JULY 28, 2020

To become a machine learning engineer, you have to interview. You have to gain relevant skills from books, courses, conferences, and projects. Include technologies, frameworks, and projects on your CV. In an interview, expect that you will be asked technical questions, insight questions, and programming questions.

Machine Learning 119

Machine Learning Artificial Inteligence Engineering How To 119

Cloudera

NOVEMBER 17, 2021

You know the one, the mathematician / statistician / computer scientist / data engineer / industry expert. Some companies are starting to segregate the responsibilities of the unicorn data scientist into multiple roles (data engineer, ML engineer, ML architect, visualization developer, etc.),

Machine Learning 124

Machine Learning Artificial Inteligence Hotels Data Engineering 124

TechCrunch

JUNE 2, 2021

The core idea behind Iterative is to provide data scientists and data engineers with a platform that closely resembles a modern GitOps-driven development stack. After spending time in academia, Iterative co-founder and CEO Dmitry Petrov joined Microsoft as a data scientist on the Bing team in 2013.

Artificial Inteligence 249

Artificial Inteligence Machine Learning Open Source Data Engineering 249

Hacker Earth Developers Blog

JUNE 26, 2019

Data science is an interdisciplinary field that uses a blend of data inference and algorithm development to solve complex analytical problems. An ideal candidate has skills in the 3 fields: mathematics/ statistics/ machine learning/ programming and business/ domain knowledge. . Machine Learning and Programming.

Data 200

Data How To Artificial Inteligence Machine Learning 200

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

O'Reilly Media - Ideas

NOVEMBER 13, 2018

As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. Privacy and security.

Machine Learning 111

Machine Learning Artificial Inteligence Software Review Conference 111

TechCrunch

OCTOBER 19, 2021

While collaborating with product developers, Dang and Wang saw that while product developers wanted to use AI, they didn’t have the right tools in which to do it without relying on data scientists. “We They didn’t work with machine learning extensively, so we decided to build tools for technical non-experts.

Artificial Inteligence 248

Artificial Inteligence Machine Learning Tools Technical Review 248

Altexsoft

JUNE 29, 2021

In a world fueled by disruptive technologies, no wonder businesses heavily rely on machine learning. Google, in turn, uses the Google Neural Machine Translation (GNMT) system, powered by ML, reducing error rates by up to 60 percent. The role of a machine learning engineer in the data science team.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Cloudera

NOVEMBER 19, 2021

We are excited by the endless possibilities of machine learning (ML). We recognise that experimentation is an important component of any enterprise machine learning practice. This is why companies spend so much time and energy figuring out how to address this so-called “last mile” problem.

Machine Learning 122

Machine Learning Artificial Inteligence eBook Data Engineering 122

CIO

APRIL 2, 2025

The spectrum is broad, ranging from process automation using machine learning models to setting up chatbots and performing complex analyses using deep learning methods. In this context, collaboration between data engineers, software developers and technical experts is particularly important.

Artificial Inteligence 120

Artificial Inteligence Technical Advisors Artificial Intelligence Automotive 120

Cloudera

APRIL 13, 2021

You’ve probably heard it more than once: Machine learning (ML) can take your digital transformation to another level. We recently published a Cloudera Special Edition of Production Machine Learning For Dummies eBook. Let your teams experiment rapidly, fail early and often, continuously learn, and try new things.

Machine Learning 98

Machine Learning Artificial Inteligence Enterprise eBook 98

CIO

OCTOBER 13, 2023

Information/data governance architect: These individuals establish and enforce data governance policies and procedures. Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence.

Data 199

Data Data Engineering Database Administration Artificial Inteligence 199

Altexsoft

JUNE 25, 2019

Being at the top of data science capabilities, machine learning and artificial intelligence are buzzing technologies many organizations are eager to adopt. If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Cloudera

JANUARY 6, 2021

Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle.

Machine Learning 133

Machine Learning Artificial Inteligence Data Applications 133

CIO

JUNE 11, 2024

One of the certifications, AWS Certified AI Practitioner, is a foundational-level certification to help workers from a variety of backgrounds to demonstrate that they understand AI and generative AI concepts, can recognize opportunities that benefit from AI, and know how to use AI tools responsibly.

Artificial Inteligence 173

Artificial Inteligence AWS Artificial Intelligence Machine Learning 173

Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Artificial Inteligence 98

d2iq

FEBRUARY 19, 2021

Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

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 195

Analytics Data Engineering Artificial Inteligence Machine Learning 195

O'Reilly Media - Ideas

APRIL 9, 2019

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. I agree; learn as much as you can.

Data Engineering 112

Data Engineering Engineering Data Technical Review 112

CIO

NOVEMBER 27, 2024

For AI, there’s no universal standard for when data is ‘clean enough.’ An organization can undermine itself by trying to get its data ready for AI before starting work on understanding and building out its AI use cases, Carlsson cautions. You could, in theory, be cleaning forever, depending on the size of your data,” he says.

Data 211

Data Enterprise Weak Development Team Software Review 211

AWS Machine Learning - AI

NOVEMBER 15, 2024

The flexible, scalable nature of AWS services makes it straightforward to continually refine the platform through improvements to the machine learning models and addition of new features. Dr. Nicki Susman is a Senior Machine Learning Engineer and the Technical Lead of the Principal AI Enablement team.

Generative AI 111

Generative AI AWS Groups Artificial Inteligence 111

CIO

JUNE 10, 2024

IT leaders need talent that knows how to enable and manage AI capabilities being built into enterprise applications. They also need workers who know how those capabilities can serve the business. Moreover, many need deeper AI-related skills, too, such as for building machine learning models to serve niche business requirements.

Artificial Inteligence 204

Artificial Inteligence Strategy Machine Learning Training 204

Xebia

DECEMBER 23, 2024

Diverse User Roles and Decentralized Teams: Amplifying the Cost Challenge One of the greatest strengths of modern data platforms is their ability to support a wide variety of usersdata engineers, analysts, scientists, and even business stakeholders. Upskilling Teams: Go beyond awareness by providing targeted training and resources.

Data 130

Data Storage Culture Resources 130

CIO

APRIL 22, 2022

What is data science? Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Organizations need data scientists and analysts with expertise in techniques for analyzing data.

Data 210

Data Artificial Inteligence Machine Learning Analytics 210

Cloudera

JANUARY 20, 2021

For more context, this demo is based on concepts discussed in this blog post How to deploy ML models to production. Machine learning is now being used to solve many real-time problems. One big use case is with sensor data. How to Run This Demo Application. Background / Overview. GitHub Repo Link.

Machine Learning 115

Machine Learning Artificial Inteligence Applications Data 115

Xebia

DECEMBER 23, 2024

Diverse User Roles and Decentralized Teams: Amplifying the Cost Challenge One of the greatest strengths of modern data platforms is their ability to support a wide variety of usersdata engineers, analysts, scientists, and even business stakeholders. Upskilling Teams: Go beyond awareness by providing targeted training and resources.

Data 130

Data Storage Culture Resources 130

UruIT

JULY 23, 2019

Most recommended development and deployment platforms for machine learning projects. Are you getting started with Machine Learning? There’s a forecasted demand for Machine Learning among all kinds of industries. Innovative machine learning products and services on a trusted platform.

Artificial Inteligence 81

Artificial Inteligence Machine Learning Azure Software Review 81

CIO

JUNE 7, 2022

Data scientists are the core of any AI team. They process and analyze data, build machine learning (ML) models, and draw conclusions to improve ML models already in production. Data engineer. Data engineers build and maintain the systems that make up an organization’s data infrastructure.

Artificial Inteligence 218

Artificial Inteligence Technical Review Fractional CTO Data Engineering 218

CIO

APRIL 12, 2023

Real-time AI involves processing data for making decisions within a given time frame. Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. It isn’t easy.

Artificial Inteligence 218

Artificial Inteligence Artificial Intelligence Machine Learning Agile 218

CIO

SEPTEMBER 29, 2023

Understanding how to leverage ChatGPT in the workplace has quickly become an increasingly valuable skill that companies are interested in capitalizing on to achieve business goals. Most relevant roles for making use of NLP include data scientist , machine learning engineer, software engineer, data analyst , and software developer.

Generative AI 214

Generative AI Artificial Inteligence Machine Learning ChatGPT 214

O'Reilly Media - Data

AUGUST 24, 2018

Machine learning and AI technologies and platforms at AWS. Dan Romuald Mbanga walks through the ecosystem around the machine learning platform and API services at AWS. Watch " Machine learning and AI technologies and platforms at AWS.". Democratizing data. Watch " Why contribute to open source? ".

Open Source 155

Open Source Journal Artificial Inteligence Machine Learning 155

TechCrunch

DECEMBER 10, 2020

” It currently has a database of some 180,000 engineers covering around 100 or so engineering skills, including React, Node, Python, Agular, Swift, Android, Java, Rails, Golang, PHP, Vue, DevOps, machine learning, data engineering and more.

Engineering 325

Engineering Artificial Inteligence Lambda Machine Learning 325

CIO

JANUARY 19, 2024

The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. The exam is designed for seasoned and high-achiever data science thought and practice leaders.

Artificial Inteligence 190

Artificial Inteligence Data Machine Learning Azure 190

CIO

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. Organization: AWS Price: US$300 How to prepare: Amazon offers free exam guides, sample questions, practice tests, and digital training.

Big Data 190

Big Data Analytics Data eLearning 190

CIO

NOVEMBER 29, 2022

For data warehouses, it can be a wide column analytical table. Many companies reach a point where the rate of complexity exceeds the ability of data engineers and architects to support the data change management speed required for the business. Data or derivatives of the data can also flow back into the data ecosystem.

Organization 167

Organization Technical Review Data Artificial Inteligence 167