O'Reilly Media - Ideas

MAY 1, 2019

Learn new topics and refine your skills with more than 160 new live online training courses we opened up for May and June on the O'Reilly online learning platform. Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , May 20. First Steps in Data Analysis , May 20.

Course 47

Course Training Artificial Inteligence Machine Learning 47

Altexsoft

FEBRUARY 11, 2023

Data architect and other data science roles compared Data architect vs data engineer Data engineer is an IT specialist that develops, tests, and maintains data pipelines to bring together data from various sources and make it available for data scientists and other specialists.

Data 87

Data Data Engineering Big Data Architecture 87

Altexsoft

JUNE 29, 2021

MLEs are usually a part of a data science team which includes data engineers , data architects, data and business analysts, and data scientists. Who does what in a data science team. Machine learning engineers are relatively new to data-driven companies.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Altexsoft

JULY 23, 2020

It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. MLOps lies at the confluence of ML, data engineering, and DevOps.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

O'Reilly Media - Data

JULY 10, 2018

Data scientists, data engineers, AI and ML developers, and other data professionals need to live ethical values, not just talk about them. The hard thing about being an ethical data scientist isn’t understanding ethics. It’s doing good data science. It’s the junction between ethical ideas and practice.

Data 173

Data Weak Development Team Software Review Culture 173

d2iq

FEBRUARY 19, 2021

Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

Dataiku

MAY 20, 2020

Remote work is the ultimate litmus test of the data organization’s robustness. The Challenges of Remote Data Science. Collaboration across teams : Data projects are not only about data, but also require strong involvement from business teams to build experience, generate buy-in, and validate relevance.

Data 105

Data How To Artificial Inteligence Machine Learning 105

Altexsoft

OCTOBER 30, 2021

Engineers are not only the ones bearing helmets and operating on construction sites. Scientists don’t always wear lab coats or handle test tubes. Explaining the difference, especially when they both work with something intangible such as data , is difficult. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Artificial Inteligence 98

Mobilunity

MAY 8, 2023

Storage Optimization focuses on optimizing data storage in the data lake environment. It involves implementing compression techniques, data partitioning, and other strategies to reduce storage costs and improve performance. It includes data validation, schema validation, and metadata management.

Engineering 52

Engineering Data Storage AWS 52

Cloudera

MARCH 28, 2023

How Data Drives Precision Healthcare One of the key advantages of precision healthcare is the ability to use large datasets to identify patients at a higher risk of developing a particular disease. This can be a tedious process open to interpretive or perception errors.

Healthcare 65

Healthcare Data Artificial Inteligence Machine Learning 65

Netflix Tech

MARCH 2, 2021

Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group. Learning through data is in Netflix’s DNA. We use A/B tests to introduce new product features, such as our daily Top 10 row that help our members discover their next favorite show.

Machine Learning 83

Machine Learning Artificial Inteligence Culture Analysis 83

O'Reilly Media - Ideas

MARCH 6, 2019

Learn new topics and refine your skills with more than 170 new live online training courses we opened up for March and April on the O'Reilly online learning platform. Certified Blockchain Solutions Architect (CBSA) Certification Crash Course , April 2. Data science and data tools. Data Structures in Java , April 1.

Course 11

Course Artificial Inteligence Training Microservices 11

Netflix Tech

SEPTEMBER 18, 2020

Over the course of the four years it became clear that I enjoyed combining analytical skills with solving real world problems, so a PhD in Statistics was a natural next step. I focus on improving experimentation methodology to test how well the newest files are working: do they need less bits to stream while providing a higher video quality?

Data 89

Data Analytics Culture Video 89

Apiumhub

AUGUST 12, 2021

This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Erik Bernhardsson

OCTOBER 7, 2018

For instance, this is useful when you’re running an A/B test – if you want to detect a 1% difference then you need something on the order of samples. For the sake of the argument, let’s say we’re running an A/B test that has some impact, and that we’re trying to understand the impact on conversion rate by state. number from?

Groups 267

Groups Software Review Data Testing 267

O'Reilly Media - Ideas

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Some of the best lessons are captured in Ron Kohavi, Diane Tang, and Ya Xu’s book: Trustworthy Online Controlled Experiments : A Practical Guide to A/B Testing.

Marketing 145

Marketing Weak Development Team Metrics UI/UX 145

Cloudera

DECEMBER 20, 2022

To learn more: Read how utilities lever Cloudera to manage smart meters data. Try Cloudera DataFlow (CDF), Cloudera Data Warehouse (CDW), Cloudera Data Engineering (CDE), and Cloudera Machine Learning (CML) by signing up for a 60 day trial , or test drive CDP.

Energy 80

Energy Analytics Data Artificial Inteligence 80

Erik Bernhardsson

OCTOBER 27, 2015

There’s no clear problem formulation, no clear loss function, lots of various data sets to use. Of course you’re going to waste too much time doing something that turns out to nothing. So it really just boils down to doing lots of highly informed A/B tests. How do you respond when you hear the phrase ‘big data’?

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

There’s no clear problem formulation, no clear loss function, lots of various data sets to use. Of course you’re going to waste too much time doing something that turns out to nothing. So it really just boils down to doing lots of highly informed A/B tests. How do you respond when you hear the phrase ‘big data’?

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Altexsoft

APRIL 13, 2023

But of course, you can only share data you have yourself – so higher visibility leads to higher transparency. To get a better picture, check out a short explainer of what data engineering is about Data analytics Now that we have all this data, we can finally work on the actual witchcraft. Data siloes.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

DataRobot

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

Marcusoft

SEPTEMBER 10, 2019

He is a brilliant programmer, data engineer, agile aficionado and he keeps my argumentation sharp with his analytic abilities. There’s nothing wrong in measuring that flow time of course, but we should recognize that it is not done. Or testing. This is one story that I’ve told many times and I wanted to share it here too.

Agile 40

Agile Transportation Coaching Data Engineering 40

OpenCredo

JULY 13, 2018

User engagement and acceptance testing is talked about, but it never really materialises. We were asked to iron out some of the creases in a new Data Producer platform involving one of the Data Consumer pipelines (let’s call it Project Datatron). At first it looked like a fairly straightforward data engineering problem.

Architecture 40

Architecture Fractional CTO CTO Coach Engineering 40

Altexsoft

AUGUST 25, 2021

Which of course means that there’s an abundance of research in this area. These won’t be the texts as we see them, of course. There are two main steps for preparing data for the machine to understand. Any ML project starts with data preparation. Language modeling. Text annotation and formatting. High level of expertise.

Tools 139

Tools Artificial Inteligence Technical Review Systems Review 139

Erik Bernhardsson

OCTOBER 7, 2018

For instance, this is useful when you’re running an A/B test – if you want to detect a 1% difference then you need something on the order of samples. For the sake of the argument, let’s say we’re running an A/B test that has some impact, and that we’re trying to understand the impact on conversion rate by state. number from?

Groups 100

Groups Software Review Data Testing 100

Altexsoft

AUGUST 29, 2023

This article explains what a data lake is, its architecture, and diverse use cases. The goal is to provide a comprehensive guide that can be a navigational tool for all specialists plotting their course in today’s data-driven world. What is a data lake? Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Artificial Inteligence 52

Xebia

FEBRUARY 25, 2024

DevOps may sound familiar, but nowadays there are a lot more terms: LLMOps, LegOps (no, not Lego-Ops), and of course MLOps. Data science is generally not operationalized Consider a data flow from a machine or process, all the way to an end-user. Containerization Now, we can serve our model and send data (e.g.

Applications 130

Applications Technical Review Software Review Azure 130

Existek

SEPTEMBER 28, 2023

Like any other developer, the role of AI experts embraces creating, testing, and deploying code. Using prepared data, AI software developers can implement techniques to evaluate and optimize model performance. It can often involve feature engineering to support relevant functionality. “What do AI developers do?”

Artificial Inteligence 52

Artificial Inteligence Development How To Artificial Intelligence 52

Altexsoft

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. Their role entails transforming, testing, and documenting data.

Analytics 59

Analytics Engineering Data Engineering Software Engineering 59

Linux Academy

MAY 7, 2019

Microsoft Certified Azure AI Engineer Associate ( Associate ). Microsoft Certified Azure Data Engineer Associate ( Associate ). Linux Academy released a course for the AZ-900 exam in May 2019. Linux Academy will be releasing a course for the AZ-103 exam by the end of Q2 2019.

Azure 150

Azure Linux Technical Review Course 150

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. What is Apache Airflow?

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

Linux Academy

MAY 7, 2019

Microsoft Certified Azure AI Engineer Associate ( Associate ). Microsoft Certified Azure Data Engineer Associate ( Associate ). Linux Academy released a course for the AZ-900 exam in May 2019. Linux Academy will be releasing a course for the AZ-103 exam by the end of Q2 2019.

Azure 134

Azure Linux Technical Review Course 134

O'Reilly Media - Ideas

JANUARY 25, 2024

And, of course, design patterns are used in legacy code—even code that was written before the term was coined! Attendees included small business owners, sales and marketing personnel, and C-suite executives, along with many programmers and engineers from different disciplines. SQL Server also showed a 5.3%

Trends 121

Trends Technical Review Technology Artificial Inteligence 121

Altexsoft

AUGUST 19, 2022

Power Q&A allows you to explore your data in your own words by asking a question using natural language. Power BI is a powerful, multi-featured tool, but of course, just like anything in this world, it’s not perfect. The Good and the Bad of Selenium Test Automation Software. Q&A in Power BI. Pros of Power BI.

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Perform ELT testing. Please note!

Tools 52

Tools Software Review Systems Review Testing 52

Xebia

MAY 16, 2023

Plus, given that cloud infrastructures have (almost) nothing to do with running any code locally, testing becomes a real challenge. This means that your code can be written once — in Python, of course — and run on basically any cloud platform, making your pipeline more portable and flexible.

Cloud 130

Cloud Data Azure Open Source 130

Existek

JANUARY 11, 2022

It helps them streamline the development process by using Visual Studio, Visual Studio Code, SDKs, Azure Monitor, and Azure Load Testing. Development Operations Engineer $122 000. Senior Sofware Engineer $130 000. Software Engineer $110 000. Data Engineer $130 000. Platform Engineer $125 000.

Azure 52

Azure AWS Cloud How To 52