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5 Workflow Automation Tools for All Professionals KDnuggets

5 Workflow Automation Tools for All Professionals KDnuggets

5 Workflow Automation Tools for All ProfessionalsKDnuggets Five powerful automation tools to help you streamline repetitive digital tasks, increase productivity, and create smarter workflows without requiring deep technical skills.

 Five powerful automation tools to help you streamline repetitive digital tasks, increase productivity, and create smarter workflows without requiring deep technical skills. Read More  

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Mining business learnings for AI deployment AI News

Mining business learnings for AI deployment AI News

Mining business learnings for AI deploymentAI News Mining conglomerate BHP describes AI as the way it’s turning operational data into better day-to-day decisions. A blog post from the company highlights the analysis of data from sensors and monitoring systems to spot patterns and flag issues for plant machinery, giving choices to decision-makers that can improve efficiency and safety – plus reduce environmental
The post Mining business learnings for AI deployment appeared first on AI News.

 Mining conglomerate BHP describes AI as the way it’s turning operational data into better day-to-day decisions. A blog post from the company highlights the analysis of data from sensors and monitoring systems to spot patterns and flag issues for plant machinery, giving choices to decision-makers that can improve efficiency and safety – plus reduce environmental
The post Mining business learnings for AI deployment appeared first on AI News. Read More  

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Google to Shut Down Dark Web Monitoring Tool in February 2026 The Hacker Newsinfo@thehackernews.com (The Hacker News)

Google has announced that it’s discontinuing its dark web report tool in February 2026, less than two years after it was launched as a way for users to monitor if their personal information is found on the dark web. To that end, scans for new dark web breaches will be stopped on January 15, 2026, […]

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AWS’s legacy will be in AI success AI News

AWS’s legacy will be in AI success AI News

AWS’s legacy will be in AI successAI News As the company that kick-started the cloud computing revolution, Amazon is one of the world’s biggest companies whose practices in all things technological can be regarded as a blueprint for implementing new technology. This article looks at some of the ways that the company is deploying AI in its operations. Amazon’s latest AI strategy has
The post AWS’s legacy will be in AI success appeared first on AI News.

 As the company that kick-started the cloud computing revolution, Amazon is one of the world’s biggest companies whose practices in all things technological can be regarded as a blueprint for implementing new technology. This article looks at some of the ways that the company is deploying AI in its operations. Amazon’s latest AI strategy has
The post AWS’s legacy will be in AI success appeared first on AI News. Read More  

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Geospatial exploratory data analysis with GeoPandas and DuckDB Towards Data Science

Geospatial exploratory data analysis with GeoPandas and DuckDBTowards Data Science In this article, I’ll show you how to use two popular Python libraries to carry out some geospatial analysis of traffic accident data within the UK. I was a relatively early adopter of DuckDB, the fast OLAP database, after it became available, but only recently realised that, through an extension, it offered a large number
The post Geospatial exploratory data analysis with GeoPandas and DuckDB appeared first on Towards Data Science.

 In this article, I’ll show you how to use two popular Python libraries to carry out some geospatial analysis of traffic accident data within the UK. I was a relatively early adopter of DuckDB, the fast OLAP database, after it became available, but only recently realised that, through an extension, it offered a large number
The post Geospatial exploratory data analysis with GeoPandas and DuckDB appeared first on Towards Data Science. Read More  

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AI News & Insights Featured Image

The Machine Learning “Advent Calendar” Day 15: SVM in Excel Towards Data Science

The Machine Learning “Advent Calendar” Day 15: SVM in ExcelTowards Data Science Instead of starting with margins and geometry, this article builds the Support Vector Machine step by step from familiar models. By changing the loss function and reusing regularization, SVM appears naturally as a linear classifier trained by optimization. This perspective unifies logistic regression, SVM, and other linear models into a single, coherent framework.
The post The Machine Learning “Advent Calendar” Day 15: SVM in Excel appeared first on Towards Data Science.

 Instead of starting with margins and geometry, this article builds the Support Vector Machine step by step from familiar models. By changing the loss function and reusing regularization, SVM appears naturally as a linear classifier trained by optimization. This perspective unifies logistic regression, SVM, and other linear models into a single, coherent framework.
The post The Machine Learning “Advent Calendar” Day 15: SVM in Excel appeared first on Towards Data Science. Read More  

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Customize agent workflows with advanced orchestration techniques using Strands Agents Artificial Intelligence

Customize agent workflows with advanced orchestration techniques using Strands Agents Artificial Intelligence

Customize agent workflows with advanced orchestration techniques using Strands AgentsArtificial Intelligence In this post, we explore two powerful orchestration patterns implemented with Strands Agents. Using a common set of travel planning tools, we demonstrate how different orchestration strategies can solve the same problem through distinct reasoning approaches,

 In this post, we explore two powerful orchestration patterns implemented with Strands Agents. Using a common set of travel planning tools, we demonstrate how different orchestration strategies can solve the same problem through distinct reasoning approaches, Read More  

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Operationalize generative AI workloads and scale to hundreds of use cases with Amazon Bedrock – Part 1: GenAIOps Artificial Intelligence

Operationalize generative AI workloads and scale to hundreds of use cases with Amazon Bedrock – Part 1: GenAIOps Artificial Intelligence

Operationalize generative AI workloads and scale to hundreds of use cases with Amazon Bedrock – Part 1: GenAIOpsArtificial Intelligence In this first part of our two-part series, you’ll learn how to evolve your existing DevOps architecture for generative AI workloads and implement GenAIOps practices. We’ll showcase practical implementation strategies for different generative AI adoption levels, focusing on consuming foundation models.

 In this first part of our two-part series, you’ll learn how to evolve your existing DevOps architecture for generative AI workloads and implement GenAIOps practices. We’ll showcase practical implementation strategies for different generative AI adoption levels, focusing on consuming foundation models. Read More  

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Applying data loading best practices for ML training with Amazon S3 clients Artificial Intelligence

Applying data loading best practices for ML training with Amazon S3 clients Artificial Intelligence

Applying data loading best practices for ML training with Amazon S3 clientsArtificial Intelligence In this post, we present practical techniques and recommendations for optimizing throughput in ML training workloads that read data directly from Amazon S3 general purpose buckets.

 In this post, we present practical techniques and recommendations for optimizing throughput in ML training workloads that read data directly from Amazon S3 general purpose buckets. Read More  

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The Data Detox: Training Yourself for the Messy, Noisy, Real World KDnuggets

The Data Detox: Training Yourself for the Messy, Noisy, Real World KDnuggets

The Data Detox: Training Yourself for the Messy, Noisy, Real WorldKDnuggets In this article, we’ll use a real-life data project to explore four practical steps for preparing to deal with messy, real-life datasets.

 In this article, we’ll use a real-life data project to explore four practical steps for preparing to deal with messy, real-life datasets. Read More