Xebia

FEBRUARY 28, 2025

Universities have been pumping out Data Science grades in rapid pace and the Open Source community made ML technology easy to use and widely available. Both the tech and the skills are there: Machine Learning technology is by now easy to use and widely available. Big part of the reason lies in collaboration between teams.

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Technical Review Weak Development Team Artificial Inteligence Machine Learning 182

O'Reilly Media - Data

MAY 24, 2018

In particular, we examined the evolution of key topics covered in this podcast: data science and machine learning, data engineering and architecture, AI, and the impact of each of these areas on businesses and companies. Continue reading The evolution of data science, data engineering, and AI.

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Data Engineering Engineering Data Artificial Inteligence 161

CIO

SEPTEMBER 29, 2022

And we recognized as a company that we needed to start thinking about how we leverage advancements in technology and tremendous amounts of data across our ecosystem, and tie it with machine learning technology and other things advancing the field of analytics. But we have to bring in the right talent. more than 3,000 of themâ??that

Artificial Inteligence 201

Artificial Inteligence Machine Learning Travel Technical Review 201

TechCrunch

NOVEMBER 18, 2021

Ashish Kakran , principal at Thomvest Ventures , is a product manager/engineer turned investor who enjoys supporting founders with a balance of technical know-how, customer insights, empathy with challenges and market knowledge. In the early 2000s, most business-critical software was hosted on privately run data centers. Ashish Kakran.

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Enterprise Artificial Inteligence Data Engineering Data Center 344

CIO

SEPTEMBER 12, 2022

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 Today, NJ Transit is a “data engine on wheels,” says the CIDO. We have shown out value,” Fazal says of the transformation.

Data Engineering 174

Data Engineering Engineering Data Transportation 174

TechCrunch

DECEMBER 10, 2020

As remote work continues to solidify its place as a critical aspect of how businesses exist these days, a startup that has built a platform to help companies source and bring on one specific category of remote employees — engineers — is taking on some more funding to meet demand. Turing is essentially tapping into both concepts.

Engineering 325

Engineering Artificial Inteligence Lambda Machine Learning 325

Xebia

MARCH 30, 2025

“The fine art of data engineering lies in maintaining the balance between data availability and system performance.” ” Ted Malaska At Melexis, a global leader in advanced semiconductor solutions, the fusion of artificial intelligence (AI) and machine learning (ML) is driving a manufacturing revolution.

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Testing Artificial Inteligence Comparison Software Review 130

O'Reilly Media - Data

JULY 18, 2018

In this short talk, I describe some interesting trends in how data is valued, collected, and shared. Economic value of data. It’s no secret that companies place a lot of value on data and the data pipelines that produce key features. But if data is precious, how do we go about estimating its value?

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Artificial Inteligence Machine Learning Data Marketing 191

CIO

DECEMBER 12, 2024

While there seems to be a disconnect between business leader expectations and IT practitioner experiences, the hype around generative AI may finally give CIOs and other IT leaders the resources they need to address longstanding data problems, says TerrenPeterson, vice president of data engineering at Capital One.

Data 201

Data Survey Artificial Inteligence Education 201

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS on the Cloudera Data Platform comes pre-configured with all the necessary libraries and dependencies to bring the power of RAPIDS to your projects.

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Artificial Inteligence Machine Learning Engineering Training 137

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

CIO

DECEMBER 10, 2024

As many companies that have already adopted off-the-shelf GenAI models have found, getting these generic LLMs to work for highly specialized workflows requires a great deal of customization and integration of company-specific data. million on inference, grounding, and data integration for just proof-of-concept AI projects.

Artificial Inteligence 174

Artificial Inteligence Off-The-Shelf Insurance Analytics 174

TechCrunch

JULY 12, 2022

Machine learning can provide companies with a competitive advantage by using the data they’re collecting — for example, purchasing patterns — to generate predictions that power revenue-generating products (e.g. Del Balso says it’ll be used to scale Tecton’s engineering and go-to-market teams. “We

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Artificial Inteligence Machine Learning Marketing Data Engineering 249

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.

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Artificial Inteligence Machine Learning Engineering How To 119

Altexsoft

JULY 23, 2020

When speaking of machine learning, we typically discuss data preparation or model building. Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. MLOps lies at the confluence of ML, data engineering, and DevOps. More time for development of new models.

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Artificial Inteligence Machine Learning DevOps Tools 145

The Crazy Programmer

NOVEMBER 6, 2021

Currently, the demand for data scientists has increased 344% compared to 2013. hence, if you want to interpret and analyze big data using a fundamental understanding of machine learning and data structure. Because the salary for a data scientist can be over Rs5,50,000 to Rs17,50,000 per annum.

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Artificial Inteligence Blockchain Software Review Artificial Intelligence 290

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

Dzone - DevOps

DECEMBER 31, 2024

MLOps, or Machine Learning Operations, is a set of practices that combine machine learning (ML), data engineering, and DevOps to streamline and automate the end-to-end ML model lifecycle. MLOps is an essential aspect of the current data science workflows.

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Artificial Inteligence Machine Learning Scalability Data Engineering 96

TechCrunch

OCTOBER 7, 2021

Increasingly, conversations about big data, machine learning and artificial intelligence are going hand-in-hand with conversations about privacy and data protection. “But now we are running into the bottleneck of the data. But humans are not meant to be mined.” ”

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Artificial Inteligence Engineering Technical Review Data 246

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

Xebia

MARCH 13, 2025

The implementation was a over-engineered custom Feast implementation using unsupported backend data stores. The engineer that implemented it had left the company by the time I joined. Prevent repeated feature development work Software engineering best practice tells us Dont Repeat Yourself ( DRY ).

Training 130

Training Artificial Inteligence Machine Learning Data 130

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.),

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Artificial Inteligence Machine Learning Hotels Data Engineering 124

Altexsoft

OCTOBER 30, 2021

Was Nikola Tesla a scientist or engineer? These men didn’t stop at scientific research and ended up conceptualizing or engineering their inventions. Engineers are not only the ones bearing helmets and operating on construction sites. Data science vs data engineering. How about Edison? Or Da Vinci?

Data Engineering 98

Data Engineering Engineering Data Artificial Inteligence 98

CIO

DECEMBER 4, 2024

We’ve had folks working with machine learning and AI algorithms for decades,” says Sam Gobrail, the company’s senior director for product and technology. The new team needs data engineers and scientists, and will look outside the company to hire them. It’s best to look for somebody who’s highly adaptable,” says Gobrail.

Recruiting 202

Recruiting Artificial Inteligence Programming Technology 202

CIO

DECEMBER 20, 2024

In addition to using cloud for storage, many modern data architectures make use of cloud computing to analyze and manage data. Modern data architectures use APIs to make it easy to expose and share data. AI and machine learning models. Application programming interfaces.

Architecture 183

Architecture Data Fractional CTO Technical Review 183

TechCrunch

MAY 10, 2022

“The major challenges we see today in the industry are that machine learning projects tend to have elongated time-to-value and very low access across an organization. “Given these challenges, organizations today need to choose between two flawed approaches when it comes to developing machine learning. .

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Artificial Inteligence Machine Learning Off-The-Shelf Training 235

Netflix Tech

JUNE 20, 2024

A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024 The Data Engineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.

Data Engineering 82

Data Engineering Engineering Data Generative AI 82

Cloudera

SEPTEMBER 17, 2020

With growing disparate data across everything from edge devices to individual lines of business needing to be consolidated, curated, and delivered for downstream consumption, it’s no wonder that data engineering has become the most in-demand role across businesses — growing at an estimated rate of 50% year over year.

Data Engineering 104

Data Engineering Engineering Data Tools 104

CIO

JUNE 11, 2024

The company is offering eight free courses , leading up to this certification, including Fundamentals of Machine Learning and Artificial Intelligence, Exploring Artificial Intelligence Use Cases and Application, and Essentials of Prompt Engineering. Registration for the beta exams for the two certifications opens August 13.

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Artificial Inteligence AWS Artificial Intelligence Machine Learning 173

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.

Data 130

Data Storage Culture Resources 130

TechCrunch

MAY 3, 2022

“There were no purpose-built machine learning data tools in the market, so [we] started Galileo to build the machine learning data tooling stack, beginning with a [specialization in] unstructured data,” Chatterji told TechCrunch via email.

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Artificial Inteligence Machine Learning Development Software Review 223

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. Continuous Operations for Production Machine Learning (COPML) helps companies think about the entire life cycle of an ML model.

Artificial Inteligence 122

Artificial Inteligence Machine Learning eBook Data Engineering 122

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.

Data 130

Data Storage Culture Resources 130

TechCrunch

APRIL 12, 2022

“Searching for the right solution led the team deep into machine learning techniques, which came with requirements to use large amounts of data and deliver robust models to production consistently … The techniques used were platformized, and the solution was used widely at Lyft.” ” Taking Flyte.

Artificial Inteligence 202

Artificial Inteligence Machine Learning Open Source Biotech 202

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

Cloudera

APRIL 9, 2021

The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization. Specifically, we’ll focus on training Machine Learning (ML) models to forecast ECC part production demand across all of its factories. Data Collection – streaming data.

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Artificial Inteligence Machine Learning Data Data Engineering 98

Cloudera

OCTOBER 19, 2021

More advanced users can still continue to deploy their own customer Airflow DAGs as before, or use the Pipeline authoring UI to bootstrap their projects for further customization (as we describe later the pipeline engine generates Airflow code which can be used as starting to meet more complex scenarios). Pipeline Engine.

Data Engineering 120

Data Engineering Engineering Data Virtualization 120