Sat.Jun 21, 2025 - Fri.Jun 27, 2025

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Build a Data Cleaning & Validation Pipeline in Under 50 Lines of Python

KDnuggets

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter Build a Data Cleaning & Validation Pipeline in Under 50 Lines of Python Clean and validate messy data with a compact Python pipeline that fits into any workflow.

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Federal Judge Rules AI Training on Copyrighted Books Is Fair Use — With Key Limitations

ODSC - Open Data Science

Federal Judge Rules AI Training on Copyrighted Books Is Fair Use — With Key Limitations In a landmark decision for the generative AI industry, a federal judge has ruled that training AI models on copyrighted books qualifies as fair use under U.S. copyright law. The ruling, issued Monday by U.S. District Judge William Alsup in California’s Northern District, marks the first significant legal precedent in a series of ongoing lawsuits challenging the legality of AI training practices.

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How to Build your First LLM Application?

Analytics Vidhya

Have you ever tried to build your own Large Language Model (LLM) application? Ever wondered how people are making their own LLM application to increase their productivity? LLM applications have proven to be useful in every aspect. Building an LLM app is now within everyone’s reach. Thanks to the availability of AI models as well […] The post How to Build your First LLM Application?

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MLFlow Mastery: A Complete Guide to Experiment Tracking and Model Management

KDnuggets

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter MLFlow Mastery: A Complete Guide to Experiment Tracking and Model Management MLFlow is a tool that helps you manage machine learning projects.

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Precision in Motion: Why Process Optimization Is the Future of Manufacturing

Speaker: Jason Chester, Director, Product Management

In today’s manufacturing landscape, staying competitive means moving beyond reactive quality checks and toward real-time, data-driven process control. But what does true manufacturing process optimization look like—and why is it more urgent now than ever? Join Jason Chester in this new, thought-provoking session on how modern manufacturers are rethinking quality operations from the ground up.

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GenAI Playground at DataHack Summit 2025

Analytics Vidhya

If you were at DataHack Summit 2024, chances are you didn’t just witness the GenAI revolution – you played with it, battled it, laughed with it, and maybe even tried to flirt against it. The GenAI Playground, a DataHack Summit exclusive, was introduced in 2023 as an immersive creative zone. It quickly became the most […] The post GenAI Playground at DataHack Summit 2025 appeared first on Analytics Vidhya.

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Muvera: Making multi-vector retrieval as fast as single-vector search

Hacker News

Jump to Content Research Research Who we are Back to Who we are menu Defining the technology of today and tomorrow. Philosophy We strive to create an environment conducive to many different types of research across many different time scales and levels of risk. Learn more about our Philosophy Learn more Philosophy People Our researchers drive advancements in computer science through both fundamental and applied research.

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How to Combine Streamlit, Pandas, and Plotly for Interactive Data Apps

KDnuggets

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter How to Combine Streamlit, Pandas, and Plotly for Interactive Data Apps With just two Python files and a handful of methods, you can build a complete dashboard that rivals expensive business intelligence tools.

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Think Your Code Model Is Smart? Interactive Benchmarks Might Say Otherwise

NYU Center for Data Science

Letting models receive human-style feedback changed which ones ranked best by up to four spots. That is what Courant PhD student Jane Pan , CDS PhD student Jacob Pfau , CDS Assistant Professor He He , and colleagues showed in “ When Benchmarks Talk: Re-Evaluating Code LLMs with Interactive Feedback ,” which described a way to replace static coding benchmarks like HumanEval, MBPP, APPS and CodeXGLUE with a multi-step, human-in-the-loop evaluation.

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Data structures

Dataconomy

Data structures play a critical role in organizing and manipulating data efficiently, serving as the foundation for algorithms and high-performing applications. Understanding the various types of data structures and their characteristics empowers programmers to select the most appropriate tools for their specific needs, ultimately enhancing application performance and efficiency.

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Evaluating Long-Context Question & Answer Systems

Eugene Yan

eugeneyan Start Here Writing Speaking Prototyping About Evaluating Long-Context Question & Answer Systems [ llm eval survey ] · 28 min read While evaluating Q&A systems is straightforward with short paragraphs, complexity increases as documents grow larger. For example, lengthy research papers, novels and movies, as well as multi-document scenarios.

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Airflow Best Practices for ETL/ELT Pipelines

Speaker: Kenten Danas, Senior Manager, Developer Relations

ETL and ELT are some of the most common data engineering use cases, but can come with challenges like scaling, connectivity to other systems, and dynamically adapting to changing data sources. Airflow is specifically designed for moving and transforming data in ETL/ELT pipelines, and new features in Airflow 3.0 like assets, backfills, and event-driven scheduling make orchestrating ETL/ELT pipelines easier than ever!

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Automate Data Quality Reports with n8n: From CSV to Professional Analysis

KDnuggets

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter Automate Data Quality Reports with n8n: From CSV to Professional Analysis Analyze any CSV dataset from a URL and generate professional quality reports with n8n By Vinod Chugani on June 26, 2025 in Data Science Image by Author | ChatGPT The Data Quali

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Fault Tolerant Llama training

Hacker News

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Data set

Dataconomy

Data sets play a pivotal role in various fields, facilitating the extraction of valuable insights from organized information. They serve as the backbone of analytics, powering not only business intelligence but also machine learning applications. Understanding the structure, types, and formats of data sets is essential for anyone looking to leverage data effectively.

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Building Production-Ready Observability for vLLM

IBM Data Science in Practice

Monitor, trace, and visualize vLLM using OpenTelemetry, Prometheus, Grafana, and Jaeger for robust, scalable, and LLM operations. Picture this: You’ve just deployed a shiny new Large Language Model using vLLM, generating responses faster than you ever imagined. But then, during peak traffic, something goes wrong. Responses slow to a crawl, costs spiral out of control, and you’re left scrambling to figure out what happened.

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Whats New in Apache Airflow 3.0 –– And How Will It Reshape Your Data Workflows?

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.

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10 FREE AI Tools That’ll Save You 10+ Hours a Week

KDnuggets

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter 10 FREE AI Tools That’ll Save You 10+ Hours a Week No tech skills needed. Just tools that work, free to use, and actually helpful in your daily work life.

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7 AI Agent Frameworks for Machine Learning Workflows in 2025

Machine Learning Mastery

Machine learning practitioners spend countless hours on repetitive tasks: monitoring model performance, retraining pipelines, data quality checks, and experiment tracking.

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Stream processing

Dataconomy

Stream processing has become a crucial technique in today’s data-driven world, allowing organizations to harness the power of continuous streams of data. This method not only enables timely decision-making but also opens doors to innovative solutions that enhance operational efficiency. As businesses generate and receive massive amounts of data daily, stream processing emerges as a means to effectively manage and analyze this flow in real time.

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CTGT’s AI Platform Built to Eliminate Bias, Hallucinations in AI Models

insideBIGDATA

San Francisco – June 27, 2025 – CTGT, which enables enterprises to deploy AI for high-risk use cases, announced today an upgrade to its platform designed to remove bias, hallucinations and other unwanted model features from DeepSeek and other open source AI models.

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

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.

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LLM Observability: Key Practices, Tools, and Challenges

Snorkel AI

Large language models (LLMs) are transforming enterprise applications across industries. But their unique behavior creates equally unique challenges for monitoring, evaluation, and improvement. Traditional machine learning observability methods do not offer the level of insight, precision, or business alignment that enterprise generative AI (GenAI) systems require.

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'Quantum AI' algorithms already outpace the fastest supercomputers, study says

Flipboard

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AlphaGenome reshapes how scientists interpret mutations

Dataconomy

A new artificial intelligence tool, AlphaGenome , has been introduced to predict how DNA sequence variations impact gene regulation, now available via API for non-commercial research. The genome functions as the cellular instruction manual, containing the complete set of DNA that directs an organism’s appearance, function, growth, and reproduction.

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LayerNorm and RMS Norm in Transformer Models

Machine Learning Mastery

This post is divided into five parts; they are: • Why Normalization is Needed in Transformers • LayerNorm and Its Implementation • Adaptive LayerNorm • RMS Norm and Its Implementation • Using PyTorch's Built-in Normalization Normalization layers improve model quality in deep learning.

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How to Modernize Manufacturing Without Losing Control

Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives

Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri

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Power Your LLM Training and Evaluation with the New SageMaker AI Generative AI Tools

AWS Machine Learning Blog

Today we are excited to introduce the Text Ranking and Question and Answer UI templates to SageMaker AI customers. The Text Ranking template enables human annotators to rank multiple responses from a large language model (LLM) based on custom criteria, such as relevance, clarity, or factual accuracy. This ranked feedback provides critical insights that help refine models through Reinforcement Learning from Human Feedback (RLHF), generating responses that better align with human preferences.

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10 Stackable Credentials To Stand Out In Today’s AI-Driven Job Market

Flipboard

In today’s career landscape, where AI is transforming industries at lightning speed, education is no longer a one-and-done proposition. The traditional four-year degree still has value, but for many workers, it’s no longer the only pathway to career advancement.

AI 101
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Empiricism

Dataconomy

Empiricism stands as a key pillar in the study of knowledge, influencing a variety of disciplines from science to philosophy. At its core, it stresses the importance of experience and observation in understanding the world around us. By relying on sensory data and empirical research, practitioners can draw conclusions that are grounded in reality rather than abstract reasoning or intuition.

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How to Pick the PERFECT Agentic Design Pattern for Your Task

Analytics Vidhya

Imagine after months of hard work in building an AI system, you see it crumble when faced with real-world problems, and all that work goes to waste. The possible one to blame? Choosing the wrong architectural pattern. The agentic design pattern is what distinguishes purely data-processing systems from those that can truly act intelligently in […] The post How to Pick the PERFECT Agentic Design Pattern for Your Task appeared first on Analytics Vidhya.

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What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

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.

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What the Rise of AI Web Scrapers Means for Data Teams

Smart Data Collective

Cookies help us display personalized product recommendations and ensure you have great shopping experience. Accept X By using this site, you agree to the Privacy Policy and Terms of Use. Accept Analytics Analytics Show More Improving LinkedIn Ad Strategies with Data Analytics 9 Min Read Data Helps Speech-Language Pathologists Deliver Better Results 6 Min Read How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity 8 Min Read Data Analytics Is Revolutionizing Medical Cred

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LLM Observability: Key Practices, Tools, and Challenges

Snorkel AI

Large language models (LLMs) are transforming enterprise applications across industries. But their unique behavior creates equally unique challenges for monitoring, evaluation, and improvement. Traditional machine learning observability methods do not offer the level of insight, precision, or business alignment that enterprise generative AI (GenAI) systems require.

ML 52
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Entity relationship diagram (ERD)

Dataconomy

Entity relationship diagrams (ERDs) are not just tools for developers; they serve as blueprints that help organizations visualize how different data elements relate to one another. This graphical representation plays a critical role in data modeling, demonstrating the complex interplay of entities, attributes, and relationships within various systems.

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12 AI Tools Everyone is Using in 2025

Analytics Vidhya

In 2025, there’s a new AI tool for everything – text, images, coding, video, you name it, and professionals are eager to know “what’s the best tool for making their work easy?” This topic stays hot as long as generative AI keeps evolving. Everyone’s hunting for the latest AI tools to boost productivity and creativity. […] The post 12 AI Tools Everyone is Using in 2025 appeared first on Analytics Vidhya.

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A Guide to Debugging Apache Airflow® DAGs

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