Sat.Jun 07, 2025 - Fri.Jun 13, 2025

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Selling Your Side Project? 10 Marketplaces Data Scientists Need to Know

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 Selling Your Side Project? 10 Marketplaces Data Scientists Need to Know That app collecting dust on your GitHub?

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Accelerate Machine Learning Model Serving With FastAPI and Redis Caching

Analytics Vidhya

Ever waited too long for a model to return predictions? We have all been there. Machine learning models, especially the large, complex ones, can be painfully slow to serve in real time. Users, on the other hand, expect instant feedback. That’s where latency becomes a real problem. Technically speaking, one of the biggest problems is […] The post Accelerate Machine Learning Model Serving With FastAPI and Redis Caching appeared first on Analytics Vidhya.

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What Is a Lakebase?

databricks

Skip to main content Login Why Databricks Discover For Executives For Startups Lakehouse Architecture Mosaic Research Customers Customer Stories Partners Cloud Providers Databricks on AWS, Azure, GCP, and SAP Consulting & System Integrators Experts to build, deploy and migrate to Databricks Technology Partners Connect your existing tools to your Lakehouse C&SI Partner Program Build, deploy or migrate to the Lakehouse Data Partners Access the ecosystem of data consumers Partner Solutions

Database 213
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Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents

Hacker News

Today's AI systems have human-designed, fixed architectures and cannot autonomously and continuously improve themselves. The advance of AI could itself be automated. If done safely, that would accelerate AI development and allow us to reap its benefits much sooner. Meta-learning can automate the discovery of novel algorithms, but is limited by first-order improvements and the human design of a suitable search space.

Algorithm 138
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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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Implementing Vector Search from Scratch: A Step-by-Step Tutorial

Machine Learning Mastery

There’s no doubt that search is one of the most fundamental problems in computing.

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Data exploration

Dataconomy

Data exploration serves as the gateway to understanding the wealth of information hidden within datasets. By employing various techniques and tools, analysts can uncover insights that drive decision-making and improve outcomes across multiple sectors. Through careful examination of data, organizations can identify trends, detect anomalies, and derive strategic advantages.

More Trending

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Building a Custom PDF Parser with PyPDF and LangChain

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 Building a Custom PDF Parser with PyPDF and LangChain PDFs look simple — until you try to parse one.

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Mosaic AI Announcements at Data + AI Summit 2025

databricks

Skip to main content Login Why Databricks Discover For Executives For Startups Lakehouse Architecture Mosaic Research Customers Customer Stories Partners Cloud Providers Databricks on AWS, Azure, GCP, and SAP Consulting & System Integrators Experts to build, deploy and migrate to Databricks Technology Partners Connect your existing tools to your Lakehouse C&SI Partner Program Build, deploy or migrate to the Lakehouse Data Partners Access the ecosystem of data consumers Partner Solutions

AI 276
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Image recognition

Dataconomy

Image recognition is transforming how we interact with technology, enabling machines to interpret and identify what they see, similar to human vision. This remarkable capability has applications ranging from security and healthcare to social media and augmented reality. Understanding how this technology works can provide valuable insights into its potential and implications.

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Log-Linear Attention

Hacker News

The attention mechanism in Transformers is an important primitive for accurate and scalable sequence modeling. Its quadratic-compute and linear-memory complexity however remain significant bottlenecks. Linear attention and state-space models enable linear-time, constant-memory sequence modeling and can moreover be trained efficiently through matmul-rich parallelization across sequence length.

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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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Bridging the Gap: New Datasets Push Recommender Research Toward Real-World Scale

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 Bridging the Gap: New Datasets Push Recommender Research Toward Real-World Scale Publicly available datasets in recommender research currently shaping the field.

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20 Behavioral Questions to Ace Your Next Data Science Interview

Analytics Vidhya

Landing a data science role isn’t just about coding and modeling anymore. Interviewers increasingly focus on behavioral questions to assess your problem-solving, communication, and teamworking skills. In this article, we’ll explore what these questions are, why they matter, and how to answer them using proven techniques. I’ll also provide you with 20 sample behavioral questions […] The post 20 Behavioral Questions to Ace Your Next Data Science Interview appeared first on Analyt

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Data dredging

Dataconomy

Data dredging is a term that raises important conversations about the integrity of research practices. In an age where vast amounts of data are generated and analyzed, the potential for uncovering misleading relationships becomes significant. Researchers may uncover statistically significant results without any prior hypothesis, leading to questions on the viability and ethics of their findings.

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How to Work Smarter, Not Harder, with Artificial Intelligence

Flipboard

Skip to main content Skip to secondary menu Skip to primary sidebar Skip to footer Geeky Gadgets The Latest Technology News Home Top News AI Apple Android Technology Guides Gadgets Hardware Gaming Autos Deals About How to Work Smarter, Not Harder, with Artificial Intelligence 1:22 pm June 13, 2025 By Julian Horsey What if the future of work isn’t about competing with machines, but mastering the skills to work alongside them?

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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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Integrating DuckDB & Python: An Analytics Guide

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 Integrating DuckDB & Python: An Analytics Guide Learn how to run lightning-fast SQL queries on local files with ease.

Python 272
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Introducing Databricks One

databricks

Skip to main content Login Why Databricks Discover For Executives For Startups Lakehouse Architecture Mosaic Research Customers Customer Stories Partners Cloud Providers Databricks on AWS, Azure, GCP, and SAP Consulting & System Integrators Experts to build, deploy and migrate to Databricks Technology Partners Connect your existing tools to your Lakehouse C&SI Partner Program Build, deploy or migrate to the Lakehouse Data Partners Access the ecosystem of data consumers Partner Solutions

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Noisy data

Dataconomy

Noisy data can create significant obstacles in the realms of data analysis and machine learning. Its presence often muddles the ability to derive meaningful insights, leading to inaccurate conclusions and ineffective models. Understanding the complexities of noisy data is essential for improving data quality and enhancing the outcomes of predictive algorithms.

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AI Agents in Analytics Workflows: Too Early or Already Behind?

Flipboard

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 AI Agents in Analytics Workflows: Too Early or Already Behind? A look at how AI agents are reshaping the data analytics workflow and whether you’re ahead or behind the curve.

Analytics 156
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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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Why You Need RAG to Stay Relevant as a Data Scientist

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 Why You Need RAG to Stay Relevant as a Data Scientist How retrieval-augmented generation (RAG) reduces LLM costs, minimises hallucinations, and keeps you employable in the age of AI.

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Introducing Agent Bricks: Auto-Optimized Agents Using Your Data

databricks

Skip to main content Login Why Databricks Discover For Executives For Startups Lakehouse Architecture Mosaic Research Customers Customer Stories Partners Cloud Providers Databricks on AWS, Azure, GCP, and SAP Consulting & System Integrators Experts to build, deploy and migrate to Databricks Technology Partners Connect your existing tools to your Lakehouse C&SI Partner Program Build, deploy or migrate to the Lakehouse Data Partners Access the ecosystem of data consumers Partner Solutions

Analytics 348
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Data virtualization

Dataconomy

Data virtualization is transforming the way organizations access and manage their data. By allowing seamless integration of information from various sources without physical data movement, businesses can gain better insights and streamline their operations. This innovative approach to data management makes it easier for companies to leverage their data assets effectively.

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NVIDIA DGX Spark : World’s First 128GB LLM Mini System with GB10 Grace Blackwell Superchip

Flipboard

Skip to main content Skip to secondary menu Skip to primary sidebar Skip to footer Geeky Gadgets The Latest Technology News Home Top News AI Apple Android Technology Guides Gadgets Hardware Gaming Autos Deals About NVIDIA DGX Spark : World’s First 128GB LLM Mini System with GB10 Grace Blackwell Superchip 8:42 am June 12, 2025 By Julian Horsey What if the future of artificial intelligence wasn’t just smarter but also smaller?

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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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Object Detection and Visual Grounding with Qwen 2.5

PyImageSearch

Home Table of Contents Object Detection and Visual Grounding with Qwen 2.5 Introduction and Types of Spatial Understanding Object Detection Visual Grounding and Counting Understanding Relationships How Spatial Understanding Works in Qwen 2.5 VL Models Prompt Structure Task-Specific Instruction Object or Feature Specification Contextual Clues or Relationships Output Requirements Model Response Format Bounding Box Coordinates (bbox_2d or point_2d) Primary Label (label), Sub-Labels, and Description

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Announcing General Availability of Databricks Apps

databricks

We’re excited to announce the General Availability of Databricks Apps, enabling customers to securely build, deploy, and scale interactive data and AI-powered applications natively on

AI 281
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Data catalog

Dataconomy

Data catalogs play a pivotal role in modern data management strategies, acting as comprehensive inventories that enhance an organization’s ability to discover and utilize data assets. By providing a centralized view of metadata, data catalogs facilitate better analytics, data governance, and decision-making processes. Let’s explore what data catalogs are and how they support organizations in managing their data effectively.

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50+ Open-Source Tools for Building AI Agents

Flipboard

Here is the list of 50+ open-source tools for building AI agents' planning brains, memory banks, action toolkits, and the glue that holds it all together.

AI 124
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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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7 Python Errors That Are Actually Features

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 7 Python Errors That Are Actually Features You never expected these Python errors to help your work, but they do!

Python 219
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Browser-Based XGBoost: Train Models Without Jupyter or IDEs

Analytics Vidhya

Nowadays, machine learning has become an integral part of various industries such as finance, healthcare, software, and data science. However, to develop a good and working ML model, setting up the necessary environments and tools is essential, and sometimes it may create many problems as well. Now, imagine training models like XGBoost directly in your […] The post Browser-Based XGBoost: Train Models Without Jupyter or IDEs appeared first on Analytics Vidhya.

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Data analytics

Dataconomy

Data analytics serves as a powerful tool in navigating the vast ocean of information available today. Organizations across industries harness the potential of data analytics to make informed decisions, optimize operations, and stay competitive in the ever-changing marketplace. This process goes beyond mere number crunching; it transforms data into actionable insights that drive strategy and innovation.

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Build Observable Data Flywheels for Production with Iguazio’s MLRun and NVIDIA NeMo Microservices

Iguazio

We are proud to announce a new integration between MLRun, the open-source AI orchestration framework, and NVIDIA NeMo microservices, by extending NVIDIA Data Flywheel Blueprint. This integration streamlines training, evaluation, fine-tuning and monitoring of AI models at scale, ensuring high-performance, low latency and lowering costs while significantly reducing the manual effort required through intelligent automation.

ML 89
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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