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10 GitHub Repositories for Mastering Agents and MCPs

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 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.

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Unlocking the Power of Data: How Databricks, WashU & Databasin Are Redefining Healthcare Innovation

databricks

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What is Context Engineering? The New Foundation for Reliable AI and RAG Systems

Data Science Dojo

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.

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Apple Machine Learning Research at ICML 2025

Machine Learning Research at Apple

Apple researchers are advancing AI and ML through fundamental research, and to support the broader research community and help accelerate progress in this field, we share much of this research through publications and engagement at conferences. Next week, the International Conference on Machine Learning (ICML) will be held in Vancouver, Canada, and Apple is proud to once again participate in this important event for the research community and to be an industry sponsor.

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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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Build a Men’s Fashion Recommendation System Using FastEmbed and Qdrant

Analytics Vidhya

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.

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Build ETL Pipelines for Data Science Workflows in About 30 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 ETL Pipelines for Data Science Workflows in About 30 Lines of Python Want to understand how ETL really works?

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Model Context Protocol (MCP) 101: How LLMs Connect to the Real World

Data Science Dojo

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.

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How AI platforms rank on data privacy in 2025

Dataconomy

A new report from Incogni evaluates the data privacy practices of today’s most widely used AI platforms. As generative AI and large language models (LLMs) become deeply embedded in everyday tools and services, the risk of unauthorized data collection and sharing has surged. Incogni’s researchers analyzed nine leading platforms using 11 criteria to understand which systems offer the most privacy-friendly experience.

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Study could lead to LLMs that are better at complex reasoning

Flipboard

Researchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.

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7 DuckDB SQL Queries That Save You Hours of Pandas Work

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 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.

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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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What is Multi-Modal Data Analysis?

Analytics Vidhya

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?

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xAI’s Grok 4: A Bold Step Forward in Powerful and Practical AI

Data Science Dojo

Artificial intelligence is evolving fast, and Grok 4 , developed by xAI (Elon Musk’s AI company), is one of the most ambitious steps forward. Designed to compete with giants like OpenAI’s GPT-4, Google’s Gemini, and Anthropic’s Claude, Grok 4 brings a unique flavor to the large language model (LLM) space: deep reasoning , multimodal understanding , and real-time integration with live data.

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Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers, and Gradient Clipping

Machine Learning Research at Apple

While federated learning (FL) and differential privacy (DP) have been extensively studied, their application to automatic speech recognition (ASR) remains largely unexplored due to the challenges in training large transformer models. Specifically, large models further exacerbate issues in FL as they are particularly susceptible to gradient heterogeneity across layers, unlike the relatively uniform gradient behavior observed in shallow models.

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Google Cloud Creates 3-Levels Of Agentic Software Coding

Adrian Bridgwater for Forbes

Newsletters Amazon Prime Day Share a News Tip Featured Featured Breaking News White House Watch Daily Cover Stories The Capital of Quantum | Paid Program AI’s Nuanced Impact And A Quest To Quantify It DNA of Success Embracing And Bracing For AI Facing A Volatile Market, C-Suites Look To The CFO For Strategic Guidance Forbes Research: 2023 Small Business Survey Your Four-Part Blueprint To Unlock AI Value In 2025 | Paid Program Forbes Insights: Your Five-Step Strategy To Unleash AI’s Value In Mark

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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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Generative AI: A Self-Study Roadmap

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 Generative AI: A Self-Study Roadmap A practical guide for developers and data practitioners to build expertise in generative AI systems, from foundation models to production deployment.

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10 GitHub LLM Repositories Every AI Engineer Should Know

Analytics Vidhya

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.

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Biomni: A General-Purpose Biomedical AI Agent

Hacker News

Biomni: a general-purpose biomedical AI agent. Contribute to snap-stanford/Biomni development by creating an account on GitHub.

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AI is changing the world faster than most realize

Flipboard

The people building AI are saying — subtly and unsubtly — that the technology is advancing more rapidly than the vast majority of people realize.

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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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Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions

Machine Learning Research at Apple

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.

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Kaggle CLI Cheat Sheet

KDnuggets

Learn the key CLI commands for automated competition submission, downloading and uploading data, running code on free cloud compute, and accessing large AI models.

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Auxia Announces AI Analyst Agent for Marketing Teams

insideBIGDATA

PALO ALTO, Calif.—June 24, 2025—Auxia, an agentic customer orchestration platform, today announced advancements to its Analyst Agent, enabling marketing teams to discover insights from their campaigns through natural language conversations that happen in real-time. Simple questions like “Which customers are most likely to upgrade?” now get immediate answers with visual explanations showing exactly why.

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ETH Zurich and EPFL to release a LLM developed on public infrastructure

Hacker News

ETH Zurich and EPFL will release a large language model (LLM) developed on public infrastructure. Trained on the “Alps” supercomputer at the Swiss National Supercomputing Centre (CSCS), the new LLM marks a milestone in open-source AI and multilingual excellence.

AI 177
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Automation, Evolved: Your New Playbook for Smarter Knowledge Work

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.

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How a big shift in training LLMs led to a capability explosion

Flipboard

Reinforcement learning, explained with a minimum of math and jargon.

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Addressing Misspecification in Simulation-based Inference through Data-driven Calibration

Machine Learning Research at Apple

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.

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Building Modern Data Lakehouses on Google Cloud with Apache Iceberg and Apache Spark

KDnuggets

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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Data Intelligence in Action: 100+ Data and AI Use Cases from Databricks Customers

databricks

Whether it’s streamlined ingestion, unified governance or AI agent evaluation, the suite of solutions available on the Data Intelligence Platform enables businesses worldwide to drive

AI 179
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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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Knowing Steam players are hoarders explains why you give Valve that 30%

Hacker News

More than likely the person buying your game is not going to play it.

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Scientists use deep learning to uncover hidden motor signs of neurodivergence

Flipboard

Diagnosing autism and attention-related conditions often takes months, if not years. But new research shows that analyzing how people move their hands during simple tasks, with the help of artificial intelligence, could offer a faster, objective path to early detection.

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CommVQ: Commutative Vector Quantization for KV Cache Compression

Machine Learning Research at Apple

Large Language Models (LLMs) are increasingly used in applications requiring long context lengths, but the key-value (KV) cache often becomes a memory bottleneck on GPUs as con- text lengths grow. To address this, we propose Commutative Vector Quantization (CommVQ) to significantly reduce memory usage for long context LLM inference. First, we leverage additive quantization by introducing a lightweight encoder and codebook to compress the KV cache, which can then be decoded with a simple matrix m

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7 Steps to Mastering Vibe Coding

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 Steps to Mastering Vibe Coding Learn how to master vibe coding in these 7 steps, and transform AI code generation into a professional superpower.

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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.