AWS Machine Learning Blog

DECEMBER 4, 2024

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. This post is cowritten with Isaac Cameron and Alex Gnibus from Tecton.

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Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

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Applied Data Science

AUGUST 2, 2021

This post is a bitesize walk-through of the 2021 Executive Guide to Data Science and AI  — a white paper packed with up-to-date advice for any CIO or CDO looking to deliver real value through data. Automation Automating data pipelines and models ➡️ 6. Download the free, unabridged version here.

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Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

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IBM Data Science in Practice

MARCH 8, 2023

The United States published a Blueprint for the AI Bill of Rights. The growth of the AI and Machine Learning (ML) industry has continued to grow at a rapid rate over recent years. This complexity is compounded even further by the need to manage data across hybrid and multi-cloud environments.

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phData

JULY 19, 2024

This article was co-written by Lawrence Liu & Safwan Islam While the title ‘ Machine Learning Engineer ’ may sound more prestigious than ‘Data Engineer’ to some, the reality is that these roles share a significant overlap. Generative AI has unlocked the value of unstructured text-based data.

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ODSC - Open Data Science

JANUARY 2, 2024

We couldn’t be more excited to announce two events that will be co-located with ODSC East in Boston this April: The Data Engineering Summit and the Ai X Innovation Summit. Data Engineering Summit Our second annual Data Engineering Summit will be in-person for the first time! Register for free today!

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ODSC - Open Data Science

JANUARY 30, 2024

Data engineering is a hot topic in the AI industry right now. And as data’s complexity and volume grow, its importance across industries will only become more noticeable. But what exactly do data engineers do? So let’s do a quick overview of the job of data engineer, and maybe you might find a new interest.

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Pickl AI

AUGUST 1, 2023

Aspiring and experienced Data Engineers alike can benefit from a curated list of books covering essential concepts and practical techniques. These 10 Best Data Engineering Books for beginners encompass a range of topics, from foundational principles to advanced data processing methods. What is Data Engineering?

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ODSC - Open Data Science

DECEMBER 19, 2023

The field of artificial intelligence is growing rapidly and with it the demand for professionals who have tangible experience in AI and AI-powered tools. A recent study by Gartner predicts that the global AI market will grow from $15.7 So let’s check out some of the top remote AI jobs for pros to look out for in 2024.

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Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Read more to know.

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IBM Journey to AI blog

JULY 30, 2024

Generative artificial intelligence (gen AI) is transforming the business world by creating new opportunities for innovation, productivity and efficiency. This guide offers a clear roadmap for businesses to begin their gen AI journey. Most teams should include at least four types of team members.

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Data Science Dojo

FEBRUARY 20, 2023

It is used by businesses across industries for a wide range of applications, including fraud prevention, marketing automation, customer service, artificial intelligence (AI), chatbots, virtual assistants, and recommendations. It provides a variety of tools for data engineering, including model training and deployment.

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ODSC - Open Data Science

JANUARY 18, 2024

Data engineering is a rapidly growing field, and there is a high demand for skilled data engineers. If you are a data scientist, you may be wondering if you can transition into data engineering. In this blog post, we will discuss how you can become a data engineer if you are a data scientist.

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ODSC - Open Data Science

FEBRUARY 6, 2024

Data engineering has become an integral part of the modern tech landscape, driving advancements and efficiencies across industries. So let’s explore the world of open-source tools for data engineers, shedding light on how these resources are shaping the future of data handling, processing, and visualization.

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ODSC - Open Data Science

DECEMBER 14, 2023

Using Guardrails for Trustworthy AI, Projected AI Trends for 2024, and the Top Remote AI Jobs in 2024 How to Use Guardrails to Design Safe and Trustworthy AI In this article, you’ll get a better understanding of guardrails within the context of this post and how to set them at each stage of AI design and development.

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AWS Machine Learning Blog

OCTOBER 24, 2024

Conventional ML development cycles take weeks to many months and requires sparse data science understanding and ML development skills. Business analysts’ ideas to use ML models often sit in prolonged backlogs because of data engineering and data science team’s bandwidth and data preparation activities.

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IBM Journey to AI blog

OCTOBER 22, 2024

Data is the differentiator as business leaders look to utilize their competitive edge as they implement generative AI (gen AI). Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement.

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ODSC - Open Data Science

FEBRUARY 15, 2024

We couldn’t be more excited to announce the first sessions for our second annual Data Engineering Summit , co-located with ODSC East this April. Join us for 2 days of talks and panels from leading experts and data engineering pioneers. Manual labor is no longer the only option for improving data.

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ODSC - Open Data Science

FEBRUARY 14, 2023

We’ve just wrapped up our first-ever Data Engineering Summit. If you weren’t able to make it, don’t worry, you can watch the sessions on-demand and keep up-to-date on essential data engineering tools and skills. It will cover why data observability matters and the tactics you can use to address it today.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Companies are finding NLP to be one of the best applications of AI regardless of industry.

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IBM Journey to AI blog

FEBRUARY 26, 2024

But with automated lineage from MANTA, financial organizations have seen as much as a 40% increase in engineering teams’ productivity after adopting lineage. Increased data pipeline observability As discussed above, there are countless threats to your organization’s bottom line.

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Flipboard

NOVEMBER 24, 2023

Data scientists and ML engineers require capable tooling and sufficient compute for their work. To pave the way for the growth of AI, BMW Group needed to make a leap regarding scalability and elasticity while reducing operational overhead, software licensing, and hardware management.

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Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Whether youre new to AI development or an experienced practitioner, this post provides step-by-step guidance and code examples to help you build more reliable AI applications. Chaithanya Maisagoni is a Senior Software Development Engineer (AI/ML) in Amazons Worldwide Returns and ReCommerce organization.

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AWS Machine Learning Blog

JUNE 18, 2024

This post presents a solution that uses a generative artificial intelligence (AI) to standardize air quality data from low-cost sensors in Africa, specifically addressing the air quality data integration problem of low-cost sensors. Having a human-in-the-loop to validate each data transformation step is optional.

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DataRobot

SEPTEMBER 14, 2021

As we see from countless examples, the demand for AI is at a fever pitch across every industry. Becoming AI-driven is no longer really optional. As AI continues to advance at such an aggressive pace, solutions built on machine learning are quickly becoming the new norm. So let’s dive in!

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O'Reilly Media

SEPTEMBER 15, 2021

In June 2021, we asked the recipients of our Data & AI Newsletter to respond to a survey about compensation. The average salary for data and AI professionals who responded to the survey was $146,000. The results are biased by the survey’s recipients (subscribers to O’Reilly’s Data & AI Newsletter ).

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Precisely

AUGUST 15, 2024

Key Takeaways Leverage AI to achieve digital transformation goals: enhanced efficiency, decision-making, customer experiences, and more. Address common challenges in managing SAP master data by using AI tools to automate SAP processes and ensure data quality. This involves various professionals.

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IBM Journey to AI blog

SEPTEMBER 2, 2024

Historically, data engineers have often prioritized building data pipelines over comprehensive monitoring and alerting. Delivering projects on time and within budget often took precedence over long-term data health. Until recently, there were few dedicated data observability tools available.

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Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. How can data engineers address these challenges directly?

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DagsHub

MARCH 21, 2024

Compliance Achievement Speed : Reached full AI policy compliance within 4 weeks. Operational Speed : Accelerated data processing pipeline, achieving a 50% increase in data processing speed. Their primary challenges included: Data inconsistencies from non-standardized documentation.

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ODSC - Open Data Science

FEBRUARY 25, 2025

As AI continues to advance at an unprecedented pace, the demand for cutting-edge skills and practical knowledge has never been greater. Whether you want to master generative AI, deploy AI agents, or streamline your machine learning pipelines with MLOps, ODSC East 2025 has something foryou.

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IBM Journey to AI blog

OCTOBER 16, 2023

Artificial intelligence (AI) adoption is still in its early stages. As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. ” Are foundation models trustworthy?

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Data Science Blog

FEBRUARY 4, 2023

If the data sources are additionally expanded to include the machines of production and logistics, much more in-depth analyses for error detection and prevention as well as for optimizing the factory in its dynamic environment become possible.

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ODSC - Open Data Science

OCTOBER 15, 2023

Here is the second half of our two-part series of companies changing the face of AI. AI is quickly scaling through dozens of industries as companies, non-profits, and governments are discovering the power of artificial intelligence. The platform includes several features that make it easy to develop and test data pipelines.

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The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. For example, neptune.ai

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