Edureka

MARCH 19, 2025

The world of artificial intelligence is changing very quickly. Zero-shot learning (ZSL) is one of the most exciting and useful new developments. Because of this new method, models can accurately guess classes they have never seen while they were training. As AI systems get smarter, they need to be able to extend beyond what they’ve seen, and zero-shot learning is great for that.

Entertainment 40

Entertainment Datasets Machine Learning Data Collection 40

Seattle Data Guy

MARCH 19, 2025

Data integration is critical for organizations of all sizes and industriesand one of the leading providers of data integration tools is Talend, which offers the flagship product Talend Studio. In 2023, Talend was acquired by Qlik, combining the two companies data integration and analytics tools under one roof. In January 2024, Talend discontinued Talend Open… Read more The post Alternatives to Talend How To Migrate Away From Talend For Your Data Pipelines appeared first on Seattle Data Gu

Data Pipeline 130

Data Pipeline Data Integration Data Big Data 130

Snowflake

MARCH 19, 2025

Nearly nine out of 10 business leaders say their organizations data ecosystems are ready to build and deploy AI, according to a recent survey. But 84% of the IT practitioners surveyed spend at least one hour a day fixing data problems. Seventy percent spend one to four hours a day remediating data issues, while 14% spend more than four hours each day.

Retail 90

Retail Media Entertainment Unstructured Data 90

Waitingforcode

MARCH 19, 2025

If you have been working with Apache Airflow already, you certainly met XComs at some point. You know, these variables that you can "exchange" between tasks within the same DAG. If after switching to Databricks Workflows for data orchestration you're wondering how to do the same, there is good news. Databricks supports this exchange capability natively with Task values.

Data 130

Data 130

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In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate

Data Pipeline

Scott Logic

MARCH 19, 2025

Investors are relying more on ESG reporting and metrics to conduct research to gain investment-critical insights. They rely on this insight to satisfy their investors and stakeholders by ensuring that they provide good investment opportunities, with low risk. A study by Nordea Equity Research reports that between 2012 and 2015, organisations with high ESG ratings outperform the lowest rated organisations by as much as 40%.

Pharmaceutical 52

Pharmaceutical Government Systems Architecture 52

KDnuggets

MARCH 19, 2025

Data is the lifeblood of Data Science and the backbone of the AI revolution. Without it, there are no models, and sophisticated algorithms are worthless because there is no data to bring their usefulness to life.

Data Science 126

Data Science Algorithm Data IT 126

Monte Carlo

MARCH 19, 2025

Monte Carlo and Databricks double-down on their partnership, helping organizations build trusted AI applications by expanding visibility into the data pipelines that fuel the Databricks Data Intelligence Platform. Announced today, Monte Carlo and Databricks are giving data + AI teams comprehensive visibility into the quality and reliability of AI systems in Databricks Data Intelligence Platform helping organizations move beyond demos to dependable AI solutions.

Unstructured Data 52

Unstructured Data Data Pipeline High Quality Data Banking 52

KDnuggets

MARCH 19, 2025

By combining AI agents, you can build an application that not only answers questions and searches the internet but also performs computations and visualizes data effectively.

Building 120

Building Data 120

Edureka

MARCH 19, 2025

The world of artificial intelligence is changing very quickly. Zero-shot learning (ZSL) is one of the most exciting and useful new developments. Because of this new method, models can accurately guess classes they have never seen while they were training. As AI systems get smarter, they need to be able to extend beyond what they’ve seen, and zero-shot learning is great for that.

Entertainment 40

Entertainment Datasets Machine Learning Data Collection 40

Tweag

MARCH 19, 2025

A new release of Liquid Haskell is out after quite an active period of development with 99 pull requests in the liquidhaskell repository, and 29 pull requests in the liquid-fixpoint repository from about ten contributors. This post is to provide an overview of the changes that made it into the latest release. There were contributions to the reflection and proof mechanisms; we got contributions to the integration with GHC; the support of cvc5 was improved when dealing with sets, bags, and maps; a

Programming 82

Programming AWS Coding Project 82

Speaker: Tamara Fingerlin, Developer Advocate

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

Data

Edureka

MARCH 19, 2025

Latent variable models are an extremely useful topic in machine learning and statistics. They contribute to the understanding of data’s hidden structures by incorporating variables that are not directly observed but inferred from observable data. These models are commonly used for dimensionality reduction, topic modeling, and generative models, among other things.

Deep Learning 40

Deep Learning Machine Learning Raw Data Coding 40

databricks

MARCH 19, 2025

Training AI models for real-world applications require vast amounts of labeled data, which can be costly, time-consuming, and difficult to obtain at scale. Synthetic data.

Building 59

Building Data Manufacturing 59

Snowflake

MARCH 19, 2025

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Entertainment 52

Entertainment Retail Media 52

Ascend.io

MARCH 19, 2025

Data engineering in 2025 isn’t just about moving datait’s about ensuring reliability, security, and scalability as data ecosystems grow in complexity. As pipelines grow more complex and AI-integrated workflows become the standard, the difference between success and chaos lies in the practices data teams adopt. The best engineering teams arent just optimizing pipelines; theyre designing resilient and scalable data architectures that minimize downtime, accelerate deployment, and enhanc

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

Systems