The average human IQ is 100. Statistical fact – not an insult. For decades, that number has quietly defined what we meant by “normal intelligence.” But in 2025, something strange is happening. Machines with no consciousness, no emotions, and no lived experience are now scoring higher than humans on ...
Agentic AI Swarm Optimization using Artificial Bee Colonization (ABC)
Using Agentic AI prompts with the Artificial Bee Colony algorithm to enhance unsupervised clustering and optimization workflows.
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Six Lessons Learned Building RAG Systems in Production
Best practices for data quality, retrieval design, and evaluation in production RAG systems
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AI agents are reshaping how we build intelligent systems. AgentOps is quickly becoming a core discipline in AI engineering. With the market expected to grow from $5B in 2024 to $50B by 2030, the demand for production-ready agentic systems is only accelerating. Unlike simple chatbots, agents can sens...
4 Ways to Supercharge Your Data Science Workflow with Google AI Studio
With concrete examples of using AI Studio Build mode to learn faster, prototype smarter, communicate clearer, and automate quicker.
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The Real Cost of Inaction: How Silos Hurt Productivity for Data Scientists (Sponsored)
The overarching goal is to maximize the return on analytical talent, shifting their focus entirely from data preparation to predictive model development, which is a necessary move if the business intends to compete in an AI-driven economy.
A Practical Toolkit for Time Series Anomaly Detection, Using Python
Here's how to detect point anomalies within each series, and identify anomalous signals across the whole bank
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The Machine Learning “Advent Calendar” Day 17: Neural Network Regressor in Excel
Neural networks often feel like black boxes. In this article, we build a neural network regressor from scratch using only Excel formulas. By making every step explicit, from forward propagation to backpropagation, we show how a neural network learns to approximate non-linear functions with just a ha...
With all the breakthroughs happening in image processing by releases such as Nano Banana, Qwen image and SAM3, OpenAI which was at the frontier of the domain a few years back, has been relatively quiet—especially in terms of its releases. With pedestrian releases and lackluster offerings, most peopl...
10 Most Downloaded Hugging Face Datasets and Their Use-cases
If you have ever trained a model, fine-tuned an LLM, or even experimented with AI on a weekend, chances are you have landed on Hugging Face. It has quietly become the GitHub of datasets – a place where developers, researchers, and data professionals go to build models and accelerate ideas. From code...
Production-Grade Observability for AI Agents: A Minimal-Code, Configuration-First Approach
LLM-as-a-Judge, regression testing, and end-to-end traceability of multi-agent LLM systems
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3 Techniques to Effectively Utilize AI Agents for Coding
Learn how to be an effective engineer with coding agents
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Meet LangSmith Assistant – Polly [An Agent for Agents]
Let’s be honest! Building AI agents is exciting but debugging them, not so much. As we are pushing the boundaries of agentic AI the complexity of our system is skyrocketing. We have all been there staring at a trace with hundreds of steps, trying to figure out why agent hallucinated or chose the wro...
8 Things To Do With Microsoft’s MarkItDown Library
Most AI projects start with one annoying chore: cleaning messy files. PDFs, Word docs, PPTs, images, audio, and spreadsheets all need to be converted into clean text before they become useful. Microsoft’s MarkItDown finally fixes this problem. In this guide, I will show you how to install it, conver...
Building AI Agents: Insights from the First Three Days of Kaggle’s Intensive Program
I’ve spent plenty of time building agentic systems. Our platform, Mentornaut, already runs on a multi-agent setup with vector stores, knowledge graphs, and user-memory features, so I thought I had the basics down. Out of curiosity, I checked out the whitepapers from Kaggle’s Agents Intensive, and th...
The Machine Learning “Advent Calendar” Day 13: LASSO and Ridge Regression in Excel
Ridge and Lasso regression are often perceived as more complex versions of linear regression. In reality, the prediction model remains exactly the same. What changes is the training objective. By adding a penalty on the coefficients, regularization forces the model to choose more stable solutions, e...