KDnuggets
JULY 11, 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 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.
ODSC - Open Data Science
JULY 11, 2025
In recent years, data analytics has become a cornerstone of competitive advantage in sports. From Moneyball’s transformative impact on baseball to real-time player tracking in basketball and football, data-driven decision-making is redefining how games are played, coached, and consumed. For data scientists, this presents not only an exciting application area but also a rich source of structured, high-quality datasets perfect for hands-on practice.
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Towards AI
JULY 11, 2025
Last Updated on July 12, 2025 by Editorial Team Author(s): Yuval Mehta Originally published on Towards AI. Photo by Kevin Ku on Unsplash Machine learning may be glamorous when you’re tuning models on Kaggle datasets or demoing GPT wrappers. But in production? It’s a grind. You’re not just building a model. You’re building a system, one that takes in unfiltered data from real users, transforms it across distributed nodes, trains a model that doesn’t crash mid-run, and pushes predictions on a dail
AWS Machine Learning Blog
JULY 11, 2025
What if you could replace hours of data analysis with a minute-long conversation? Large language models can transform how we bridge the gap between business questions and actionable data insights. For most organizations, this gap remains stubbornly wide, with business teams trapped in endless cycles—decoding metric definitions and hunting for the correct data sources to manually craft each SQL query.
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.
Machine Learning Research at Apple
JULY 11, 2025
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.
AWS Machine Learning Blog
JULY 11, 2025
In Part 1 of this series, we explored how Amazon’s Worldwide Returns & ReCommerce (WWRR) organization built the Returns & ReCommerce Data Assist (RRDA)—a generative AI solution that transforms natural language questions into validated SQL queries using Amazon Bedrock Agents. Although this capability improves data access for technical users, the WWRR organization’s journey toward truly democratized data doesn’t end there.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
AWS Machine Learning Blog
JULY 11, 2025
Managing access control in enterprise machine learning (ML) environments presents significant challenges, particularly when multiple teams share Amazon SageMaker AI resources within a single Amazon Web Services (AWS) account. Although Amazon SageMaker Studio provides user-level execution roles, this approach becomes unwieldy as organizations scale and team sizes grow.
JULY 11, 2025
Extracting information from unstructured documents at scale is a recurring business task. Common use cases include creating product feature tables from descriptions, extracting metadata from documents, and analyzing legal contracts, customer reviews, news articles, and more. A classic approach to extracting information from text is named entity recognition (NER).
AWS Machine Learning Blog
JULY 11, 2025
Fraud detection remains a significant challenge in the financial industry, requiring advanced machine learning (ML) techniques to detect fraudulent patterns while maintaining compliance with strict privacy regulations. Traditional ML models often rely on centralized data aggregation, which raises concerns about data security and regulatory constraints.
JULY 11, 2025
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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!
AWS Machine Learning Blog
JULY 11, 2025
The global fashion industry is estimated to be valued at $1.84 trillion in 2025, accounting for approximately 1.63% of the world’s GDP ( Statista, 2025 ). With such massive amounts of generated capital, so too comes the enormous potential for toxic content and misuse. In the fashion industry, teams are frequently innovating quickly, often utilizing AI.
databricks
JULY 11, 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
Data Science Dojo
JULY 11, 2025
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.
AWS Machine Learning Blog
JULY 11, 2025
Voice AI is changing the way we use technology, allowing for more natural and intuitive conversations. Meanwhile, advanced AI agents can now understand complex questions and act autonomously on our behalf. In Part 1 of this series, you learned how you can use the combination of Amazon Bedrock and Pipecat , an open source framework for voice and multimodal conversational AI agents to build applications with human-like conversational AI.
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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.
JULY 11, 2025
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AWS Machine Learning Blog
JULY 11, 2025
This post provides the theoretical foundation and practical insights needed to navigate the complexities of LLM development on Amazon SageMaker AI , helping organizations make optimal choices for their specific use cases, resource constraints, and business objectives. We also address the three fundamental aspects of LLM development: the core lifecycle stages, the spectrum of fine-tuning methodologies, and the critical alignment techniques that provide responsible AI deployment.
Machine Learning Research at Apple
JULY 11, 2025
Subword tokenization requires balancing computational efficiency and vocabulary coverage, which often leads to suboptimal performance on languages and scripts not prioritized during training. We propose to augment pretrained language models with a vocabulary-free encoder that generates input embeddings from text rendered as pixels. Through experiments on English-centric language models, we demonstrate that our approach substantially improves machine translation performance and facilitates effect
AWS Machine Learning Blog
JULY 11, 2025
Today, we announce the public preview of long-running execution (asynchronous) flow support within Amazon Bedrock Flows. With Amazon Bedrock Flows, you can link foundation models (FMs), Amazon Bedrock Prompt Management , Amazon Bedrock Agents , Amazon Bedrock Knowledge Bases , Amazon Bedrock Guardrails , and other AWS services together to build and scale predefined generative AI 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.
Hacker News
JULY 11, 2025
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.
AWS Machine Learning Blog
JULY 11, 2025
This post is co-written with Zhanghao Wu, co-creator of SkyPilot. The rapid advancement of generative AI and foundation models (FMs) has significantly increased computational resource requirements for machine learning (ML) workloads. Modern ML pipelines require efficient systems for distributing workloads across accelerated compute resources, while making sure developer productivity remains high.
JULY 11, 2025
According to the World Economic Forum, more than 85 million jobs are being displaced by automation. At the same time, 97 million new AI-powered roles are rising in their place. This is not just the future of work anymore, it is the present.
Dataconomy
JULY 11, 2025
An Apple-supported study introduces a new foundation model, the Wearable Behavior Model (WBM), trained on behavioral data from wearables to predict health conditions, demonstrating accuracy up to 92% and outperforming traditional sensor-based models in numerous tasks. The preprint paper, titled “ Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions ,” emerged from the Apple Heart and Movement Study (AHMS).
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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
Koaning.io
JULY 11, 2025
koaning.io Blog of a data person All Posts Keyboard Reviews Apps About RSS Home All Posts Keyboard Reviews Apps About RSS Introducing bespoken 2025-07-12 llm python productivity tools When used right, claude code is a huge productivity boost. Take any brainfart, and you get working tools by just writing English. And yet. there are moments when it frustrates me.
Machine Learning Research at Apple
JULY 11, 2025
Multimodal Vision-Language Models (VLMs) enable powerful applications from their fused understanding of images and language, but many perform poorly on UI tasks due to the lack of UI training data. In this paper, we adapt a recipe for generating paired text-image training data for VLMs to the UI domain by combining existing pixel-based methods with a Large Language Model (LLM).
JULY 11, 2025
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Dataconomy
JULY 11, 2025
According to TechCrunch , Amazon Web Services (AWS) is launching an AI agent marketplace next week, with Anthropic confirmed as one of its partners. This development will be officially announced at the AWS Summit in New York City on July 15, according to individuals familiar with the plans. AWS and Anthropic did not provide comments regarding this information.
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.
JULY 11, 2025
What if you could demystify one of the most fantastic technologies of our time—large language models (LLMs)—and build your own from scratch?
Hacker News
JULY 11, 2025
Comments
JULY 11, 2025
From smarter research with Perplexity to fast video edits with Descript, these AI tools don’t just save time—they multiply your creative possibilities and sharpen your thinking.
Analytics Vidhya
JULY 11, 2025
By mid-2025, the AI “arms race” is heating up, and xAI and Anthropic have both released their flagship models, Grok 4 and Claude 4. These two models are at opposite ends of the design philosophy and deployment platform, yet they are being compared against each other as they compete head-to-head on reasoning and coding benchmarks. […] The post Grok 4 vs Claude 4: Which is Better?
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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