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.

Artificial Inteligence 111

Artificial Inteligence Machine Learning Software Review Conference 111

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.

Artificial Inteligence 107

Artificial Inteligence Machine Learning Scalability Data Engineering 107

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. Conclusion.

Artificial Inteligence 290

Artificial Inteligence Blockchain Software Review Artificial Intelligence 290

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 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.

Recruiting 202

Recruiting Artificial Inteligence Programming Technology 202

InfoQ Culture Methods

FEBRUARY 22, 2022

The article explores optimizing test execution, saving machine resources, and reducing feedback time to developers. Test suites may be computationally expensive, compete with each other for available hardware, or simply be so large as to cause considerable delay until their results are available. By Gregor Endler, Marco Achtziger.

Artificial Inteligence 109

Artificial Inteligence Machine Learning Testing Development 109

O'Reilly Media - Ideas

APRIL 2, 2019

Why companies are turning to specialized machine learning tools like MLflow. A few years ago, we started publishing articles (see “Related resources” at the end of this post) on the challenges facing data teams as they start taking on more machine learning (ML) projects. The upcoming 0.9.0

Artificial Inteligence 108

Artificial Inteligence Machine Learning Government Tools 108

InfoQ Culture Methods

FEBRUARY 16, 2023

Have you ever wondered about systems based on machine learning? In those cases, testing takes a backseat. And even if testing is done, it’s done mostly by developers itself. A tester’s role is not clearly portrayed. Testers usually struggle to understand ML-based systems and explore what contributions they can make.

Artificial Inteligence 94

Artificial Inteligence Machine Learning System Testing 94

Xebia

MARCH 13, 2025

This becomes more important when a company scales and runs more machine learning models in production. Please have a look at this blog post on machine learning serving architectures if you do not know the difference. Let’s say you are a Data Scientist working in a model development environment.

Training 130

Training Artificial Inteligence Machine Learning Data 130

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

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. In this article, we explore model governance, a function of ML Operations (MLOps). Machine Learning Model Lineage. Machine Learning Model Visibility . classification problem.

Artificial Inteligence 85

Artificial Inteligence Machine Learning Weak Development Team Construction 85

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

Altexsoft

MAY 27, 2020

Machine learning (ML) history can be traced back to the 1950s, when the first neural networks and ML algorithms appeared. Analysis of more than 16.000 papers on data science by MIT technologies shows the exponential growth of machine learning during the last 20 years pumped by big data and deep learning advancements.

Artificial Inteligence 89

Artificial Inteligence Machine Learning Architecture Training 89

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

TechCrunch

FEBRUARY 2, 2022

RudderStack , a platform that focuses on helping businesses build their customer data platforms to improve their analytics and marketing efforts, today announced that it has raised a $56 million Series B round led by Insight Partners, with previous investors Kleiner Perkins and S28 Capital also participating.

Data 204

Data Artificial Inteligence Machine Learning Architecture 204

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

SEPTEMBER 29, 2023

Most relevant roles for making use of NLP include data scientist , machine learning engineer, software engineer, data analyst , and software developer. They’re also seeking skills around APIs, deep learning, machine learning, natural language processing, dialog management, and text preprocessing.

Generative AI 214

Generative AI Artificial Inteligence Machine Learning ChatGPT 214

Apiumhub

DECEMBER 9, 2024

Azure Key Vault Secrets integration with Azure Synapse Analytics enhances protection by securely storing and dealing with connection strings and credentials, permitting Azure Synapse to enter external data resources without exposing sensitive statistics. Also combines data integration with machine learning.

Azure 91

Azure Analytics Storage Artificial Inteligence 91

O'Reilly Media - Ideas

AUGUST 18, 2020

That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows. Lessons Learned from Data Warehouse and Data Engineering Platforms.

Artificial Inteligence 145

Artificial Inteligence Machine Learning Data Data Engineering 145

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

Hacker Earth Developers Blog

JUNE 26, 2019

Finding the right candidate for the Data Science role. Finding the right candidate for the role of a Data Scientist can be tricky and challenging. This article will help you understand what Data Science is and what skill sets to look for in a candidate when hiring for a Data Science role. . Data Science.

Data 200

Data How To Artificial Inteligence Machine Learning 200

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. Big data processing. maintaining data pipeline.

Big Data 75

Big Data Data Engineering Engineering Data 75

InfoQ Culture Methods

FEBRUARY 24, 2023

In this article, Tariq King describes the metaverse concept, discusses its key engineering challenges and quality concerns, and then walks through recent technological advances in AI and software testing that are helping to mitigate these challenges.

Testing 121

Testing Engineering Software Technology 121

UruIT

APRIL 27, 2020

And whether you’re a novice or an expert, in the field of technology or finance, medicine or retail, machine learning is revolutionizing your industry and doing it at a rapid pace. You may recognize the ways that Machine Learning can improve your life and work but may not know how to implement it in your own company.

Artificial Inteligence 78

Artificial Inteligence Machine Learning Azure Software Review 78

CIO

FEBRUARY 14, 2023

To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. It’s also used to deploy machine learning models, data streaming platforms, and databases.

Artificial Inteligence 174

Artificial Inteligence Strategy Data Machine Learning 174

Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

Apiumhub

JANUARY 26, 2022

Data engineer roles have gained significant popularity in recent years. Number of studies show that the number of data engineering job listings has increased by 50% over the year. And data science provides us with methods to make use of this data. Who are data engineers?

Data Engineering 52

Data Engineering Engineering Data Artificial Inteligence 52

InfoQ Culture Methods

JULY 17, 2020

To mix the power of the data and the importance of people to offer business intelligence is a key point nowadays. Innovation is not only about the most advanced technology, management and processes are the new era of startups' innovation. The result is not only the most imporant thing, the way you do it more important.

Agile 119

Agile Innovation Culture Business Intelligence 119

Netflix Tech

JULY 21, 2022

Problem Statement The purpose of this article is to give insights into analyzing and predicting “out of memory” or OOM kills on the Netflix App. We also explore graphical analysis of the labeled dataset and suggest some feature engineering and accuracy measures for future exploration.

Artificial Inteligence 75

Artificial Inteligence Machine Learning Systems Review Big Data 75

Cloudera

APRIL 30, 2021

Apache Spark is now widely used in many enterprises for building high-performance ETL and Machine Learning pipelines. Cloudera Data Engineering (CDE) is a cloud-native service purpose-built for enterprise data engineering teams. To find out more about CDE review this article. docker login [link].

Data Engineering 65

Data Engineering Engineering Data Software Review 65

InfoQ Culture Methods

JANUARY 13, 2023

This article is a summary of the 2022 software trends podcast. 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.

Trends 104

Trends Software Report Innovation 104

Altexsoft

JANUARY 27, 2022

As of today, different machine learning (and specifically deep learning) techniques capable of processing huge amounts of both historic and real-time data are used to forecast traffic flow, density, and speed. They are usually easier, faster, and cheaper to implement than machine learning ones.

Artificial Inteligence 69

Artificial Inteligence Machine Learning Transportation Network 69

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Artificial Inteligence 52

Artificial Inteligence Machine Learning Data Systems Review 52

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. As data and analytics are embedded into the fabric of business and society –from popular apps to the Internet of Things (IoT) –Spark brings essential advances to large-scale data processing.

Open Source 117

Open Source Artificial Inteligence Machine Learning Big Data 117

O'Reilly Media - Data

MARCH 22, 2018

Over the years, machine learning (ML) has come a long way, from its existence as experimental research in a purely academic setting to wide industry adoption as a means for automating solutions to real-world problems. Manifold Learning : t-Distributed Stochastic Neighbor Embedding ( t-SNE ) (see Figure 3).

Off-The-Shelf 177

Off-The-Shelf Artificial Inteligence Machine Learning Weak Development Team 177

Apiumhub

APRIL 8, 2021

As the director of Advertisement, he works to help data-driven businesses be more successful. He also writes compelling articles about Big Data and related topics for publications such as Data Science Central, DataFloq and Dataconomy. Marcus Borba is a Big Data, analytics, and data science consultant and advisor.

Artificial Inteligence 110

Artificial Inteligence Technical Advisors Data Machine Learning 110

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 108

Big Data Technology Tools Cloud 108