KDnuggets
JULY 4, 2025
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 Serve Machine Learning Models via REST APIs in Under 10 Minutes Stop leaving your models on your laptop.
databricks
JULY 7, 2025
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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insideBIGDATA
JULY 2, 2025
By Kamal Hathi, SVP and GM, Splunk Products & Technology Today’s fast-evolving digital landscape, especially with the explosive growth of AI, has rapidly added to the complexity of data management. This growing dependence on AI has not only added to complexity, but also transformed strategic data management from a competitive advantage into a business imperative.
Analytics Vidhya
JULY 7, 2025
Recommendation systems are everywhere. From Netflix and Spotify to Amazon. But what if you wanted to build a visual recommendation engine? One that looks at the image, not just the title or tags? In this article, you’ll build a men’s fashion recommendation system. It will use image embeddings and the Qdrant vector database. You’ll go […] The post Build a Men’s Fashion Recommendation System Using FastEmbed and Qdrant appeared first on Analytics Vidhya.
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!
Data Science Dojo
JULY 7, 2025
Context engineering is quickly becoming the new foundation of modern AI system design, marking a shift away from the narrow focus on prompt engineering. While prompt engineering captured early attention by helping users coax better outputs from large language models (LLMs), it is no longer sufficient for building robust, scalable, and intelligent applications.
KDnuggets
JULY 7, 2025
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 GitHub Repositories for Mastering Agents and MCPs Learn how to build your own agentic AI application with free tutorials, guides, courses, projects, example code, research papers, and more.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Machine Learning Research at Apple
JULY 9, 2025
Wearable devices record physiological and behavioral signals that can improve health predictions. While foundation models are increasingly used for such predictions, they have been primarily applied to low-level sensor data, despite behavioral data often being more informative due to their alignment with physiologically relevant timescales and quantities.
Analytics Vidhya
JULY 8, 2025
The traditional single-modal data approaches often miss important insights that are present in cross-modal relations. Multi-Modal Analysis brings together diverse sources of data, such as text, images, audio, and more similar data to provide a more complete view of an issue. This multi-modal data analysis is called multi-modal data analytics, and it improves prediction accuracy […] The post What is Multi-Modal Data Analysis?
Data Science Dojo
JULY 8, 2025
Model Context Protocol (MCP) is rapidly emerging as the foundational layer for intelligent, tool-using AI systems, especially as organizations shift from prompt engineering to context engineering. Developed by Anthropic and now adopted by major players like OpenAI and Microsoft , MCP provides a standardized, secure way for large language models (LLMs) and agentic systems to interface with external APIs, databases, applications, and tools.
KDnuggets
JULY 3, 2025
Let's take a closer look at Google Colab's new AI features, and find out how you can use them to increase your daily data workflow productivity.
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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.
Dataconomy
JULY 2, 2025
AI integration is expanding into the Linux command line, exemplified by tools like Ollama, making its presence in this environment increasingly common. The Gemini CLI tool enables users to access Google’s Gemini AI directly within their Linux terminal. This locally installed application supports various functions, including content generation, problem-solving, detailed research, and task management.
JULY 3, 2025
Skip to Content MIT Technology Review Featured Topics Newsletters Events Audio Sign in Subscribe MIT Technology Review Featured Topics Newsletters Events Audio Sign in Subscribe Opinion Don’t let hype about AI agents get ahead of reality There is enormous potential for this technology, but only if we deploy it responsibly. By Yoav Shoham archive page July 3, 2025 Sarah Rogers/MITTR | Getty Google’s recent unveiling of what it calls a “new class of agentic experiences” feels like a turning point.
Analytics Vidhya
JULY 8, 2025
Are you an AI engineer, wondering how to attain resources that can put your skills to a practical test? It might be difficult to look for the right solution for you, based on the vast amount of information out there. Hence, we present this list of all ten GitHub llm repositories every AI engineer ought […] The post 10 GitHub LLM Repositories Every AI Engineer Should Know appeared first on Analytics Vidhya.
Hacker News
JULY 3, 2025
Today, we open sourced our Zero-Knowledge Proof (ZKP) libraries, fulfilling a promise and building on our partnership with Sparkasse to support EU age assurance.
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.
KDnuggets
JULY 7, 2025
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 DuckDB SQL Queries That Save You Hours of Pandas Work See how DuckDB outperforms Pandas in real world tasks like filtering, cohort analysis and revenue modelling all within your notebook.
Dataconomy
JULY 4, 2025
Google has open-sourced its Zero-Knowledge Proof (ZKP) libraries, delivering on a commitment and leveraging a partnership with Sparkasse to support age assurance within the European Union. This initiative aims to facilitate the development of privacy-enhancing applications and digital identity solutions by developers in both private and public sectors, addressing a pressing demand.
JULY 2, 2025
To better understand human cognition, scientists trained a large language model on 10 million psychology experiment questions. It now answers questions much like we do. Companies like OpenAI and Meta are in a race to make something they like to call artificial general intelligence.
Analytics Vidhya
JULY 7, 2025
Artificial Intelligence is at an inflection point where computer vision systems are breaking out of their classical limitations. While good at recognizing objects and patterns, they have traditionally been limited when it came to making considerations of context and reasoning. Introducing Retrieval Augemented Generation (RAG) to the scenario – changing the game in the way […] The post 7 RAG Applications for Computer Vision appeared first on Analytics Vidhya.
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
Machine Learning Research at Apple
JULY 6, 2025
This paper was presented at the Workshop on Reliable and Responsible Foundation Models at ICML 2025. Large Language Models (LLMs) have demonstrated impressive generalization capabilities across various tasks, but their claim to practical relevance is still mired by concerns on their reliability. Recent works have proposed examining the activations produced by an LLM at inference time to assess whether its answer to a question is correct.
KDnuggets
JULY 2, 2025
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 5 Fun Python Projects for Absolute Beginners Bored of theory? These hands-on Python projects make learning interactive, practical, and actually enjoyable.
insideBIGDATA
JULY 2, 2025
New York, July 2, 2025 – AI-based workflow automation company fileAI today announced the launch of its public platform designed to help enterprises and SMBs understand and collect business data trapped in unstructured formats, siloed systems, disconnected databases and externally.
JULY 6, 2025
Chances are that you have unknowingly encountered compelling online content that was created, either wholly or in part, by some version of a Large …
Speaker: Frank Taliano
Documents are the backbone of enterprise operations, but they are also a common source of inefficiency. From buried insights to manual handoffs, document-based workflows can quietly stall decision-making and drain resources. For large, complex organizations, legacy systems and siloed processes create friction that AI is uniquely positioned to resolve.
databricks
JULY 2, 2025
Introduction Large Language Models (LLMs) have swiftly become essential components of modern workflows, automating tasks traditionally performed by humans.
Machine Learning Research at Apple
JULY 9, 2025
Driven by steady progress in deep generative modeling, simulation-based inference (SBI) has emerged as the workhorse for inferring the parameters of stochastic simulators. However, recent work has demonstrated that model misspecification can compromise the reliability of SBI, preventing its adoption in important applications where only misspecified simulators are available.
KDnuggets
JULY 8, 2025
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 ETL Pipelines for Data Science Workflows in About 30 Lines of Python Want to understand how ETL really works?
Machine Learning Mastery
JULY 8, 2025
When building machine learning models, most developers focus on model architectures and hyperparameter tuning.
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.
JULY 3, 2025
LLMs — the data models powering your favorite AI chatbots — don't just have social and racial biases, a new report finds, but inherent biases against democratic institutions. A recent study , published by researchers at the MIT Sloan School of Management , analyzed how six popular LLMs (including ChatGPT, Gemini, and DeepSeek) portray the state of press freedom — and, indirectly, trust in the media — in responses to user prompts.
Analytics Vidhya
JULY 5, 2025
Have you ever been stuck in a situation where you have a huge dataset and you wanted insights from it? Sounds scary, right? Getting useful insights, especially from a huge dataset, is a tall order. Imagine transforming your dataset into an interactive web application without any frontend expertise for data visualization. Gradio, when used alongside […] The post 9 Steps for Crafting an Interactive Dashboard using Python and Gradio appeared first on Analytics Vidhya.
insideBIGDATA
JULY 7, 2025
TYSONS CORNER, Va., July 3, 2025 — Today, Available Infrastructure unveiled SanQtum, which combines national security-grade cyber protection and trusted enterprise artificial intelligence (AI) capability, according to the company. In the modern era, AI-powered, machine-speed decision-making is crucial.
KDnuggets
JULY 8, 2025
Forget data silos. You can build a modern data lakehouse that gives you transactional consistency, schema evolution, and top-tier performance, all in one place with Apache Iceberg and Apache Spark.
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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
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