KDnuggets

JANUARY 30, 2025

In this article, we show you how to run parallel time series analysis with Dask, through a practical Python-based tutorial.

Python 104

Python 104

Towards Data Science

JANUARY 30, 2025

Building more efficient AI TLDR : Data-centric AI can create more efficient and accurate models. I experimented with data pruning on MNIST to classify handwritten digits. Best runs for furthest-from-centroid selection compared to full dataset. Image byauthor. What if I told you that using just 50% of your training data could achieve better results than using the fulldataset?

Database-centric 106

Database-centric Datasets Data Architecture 106

KDnuggets

JANUARY 30, 2025

Learn how to perform paper summarization with BART.

100

100

Uber Engineering

JANUARY 30, 2025

Comments

MySQL 80

MySQL 80

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

Software Engineer

databricks

JANUARY 30, 2025

Databricks was built as an open and unified platform to handle huge data workloads at a fraction of the cost of other solutions.

Data 66

Data 66

RandomTrees

JANUARY 30, 2025

The energy and utility industry is being transformed by AI technology, and it is powered by the digital revolution. One of its newest forms, Generative AI, is bolstering utility operations reliability, efficiency, and resilience. Its place in modern utilities is most evident in real-time fault detection. The utilization of Generative AI for utilities is discussed in this article, alongside smart utilities with AI , real-time monitoring AI, and AI predictive maintenance.

Utilities 52

Utilities Algorithm Machine Learning Systems 52

Striim

JANUARY 30, 2025

During a crisiswhether its a pandemic, a natural disaster, or a major supply chain breakdownswift, informed decision-making can mean the difference between regaining control and facing further escalation. Todays organizations have access to more data than ever before, and consequently are faced with the challenge of determining how to transform this tremendous stream of real-time information into actionable insights.

Systems 52

Systems Management Hospitality Healthcare 52

Towards Data Science

JANUARY 30, 2025

Stop Creating Bad DAGsOptimize Your Airflow Environment By Improving Your PythonCode Valuable tips to reduce your DAGs parse time and save resources. Photo by Dan Roizer on Unsplash Apache Airflow is one of the most popular orchestration tools in the data field, powering workflows for companies worldwide. However, anyone who has already worked with Airflow in a production environment, especially in a complex one, knows that it can occasionally present some problems and weirdbugs.

Python 48

Python Coding Google Cloud Database 48

WeCloudData

JANUARY 30, 2025

TThe integration of Artificial Intelligence (AI) and Large Language Models (LLMs), into medical diagnosis healthcare is revolutionizing patient care. But how effective are these tools when it comes to diagnosing complex medical conditions? A recent study conducted by UVA Health, in collaboration with Stanford and Harvard, dives into the diagnostic potential of AI and offers […] The post How LLMs and AI Are Shaping Medical Diagnosis appeared first on WeCloudData.

Medical 52

Medical Healthcare IT 52

Towards Data Science

JANUARY 30, 2025

How much data does AI reallyneed? TLDR : Data-centric AI can create more efficient and accurate models. I experimented with data pruning on MNIST to classify handwritten digits. Best runs for furthest-from-centroid selection compared to full dataset. Image byauthor. What if I told you that using just 50% of your training data could achieve better results than using the fulldataset?

Database-centric 40

Database-centric Datasets Data Architecture 40

Advertisement

Apache Airflow® is the open-source standard to manage workflows as code. It is a versatile tool used in companies across the world from agile startups to tech giants to flagship enterprises across all industries. Due to its widespread adoption, Airflow knowledge is paramount to success in the field of data engineering.

Datasets

Confluent

JANUARY 30, 2025

Read this Data in Motion Tour recap to get highlights and key insights from Singaporean business leaders leveraging data streaming in their organizations.

Finance 40

Finance Data 40

Towards Data Science

JANUARY 30, 2025

Stop Creating Bad DAGsOptimize Your Airflow Environment By Improving Your PythonCode Valuable tips to reduce your DAGs parse time and save resources. Photo by Dan Roizer on Unsplash Apache Airflow is one of the most popular orchestration tools in the data field, powering workflows for companies worldwide. However, anyone who has already worked with Airflow in a production environment, especially in a complex one, knows that it can occasionally present some problems and weirdbugs.

Python 40

Python Coding Google Cloud Database 40

Precisely

JANUARY 30, 2025

Key Takeaways: Prioritize metadata maturity as the foundation for scalable, impactful data governance. Recognize that artificial intelligence is a data governance accelerator and a process that must be governed to monitor ethical considerations and risk. Integrate data governance and data quality practices to create a seamless user experience and build trust in your data.

Data Governance 103

Data Governance Government Metadata Data 103

Snowflake

JANUARY 30, 2025

Across all industries, generative AI is driving innovation and transforming how we work. Use cases range from getting immediate insights from unstructured data such as images, documents and videos, to automating routine tasks so you can focus on higher-value work. Gen AI makes this all easy and accessible because anyone in an enterprise can simply interact with data by using natural language.

Unstructured Data 86

Unstructured Data Entertainment Healthcare Telecommunication 86

Speaker: Tamara Fingerlin, Developer Advocate

In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!

Data

Confessions of a Data Guy

JANUARY 30, 2025

When it comes to building modern Lake House architecture, we often get stuck in the past, doing the same old things time after time. We are human; we are lemmings; it’s just the trap we fall into. Usually, that pit we fall into is called Spark. Now, don’t get me wrong; I love Spark. We […] The post AWS Lambda + DuckDB + Polars + Daft + Rust appeared first on Confessions of a Data Guy.

AWS 100

AWS Architecture Building IT 100