Is Your Model Time-Blind? The Case for Cyclical Feature Encoding
How cyclical encoding improves machine learning prediction
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Best OCR and vision language models you can run locally that transform documents, tables, and diagrams into flawless markdown copies with benchmark-crushing accuracy.
The Machine Learning “Advent Calendar” Day 23: CNN in Excel
A step-by-step 1D CNN for text, built in Excel, where every filter, weight, and decision is fully visible.
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This article is divided into two parts; they are: • What Is Perplexity and How to Compute It • Evaluate the Perplexity of a Language Model with HellaSwag Dataset Perplexity is a measure of how well a language model predicts a sample of text.
Understanding the process behind agentic planning and task management in LangChain
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Stop Retraining Blindly: Use PSI to Build a Smarter Monitoring Pipeline
A data scientist's guide to population stability index (PSI)
The post Stop Retraining Blindly: Use PSI to Build a Smarter Monitoring Pipeline appeared first on Towards Data Science.
Google Code Wiki: Live Docs, Diagrams & Chat for Any GitHub Repo
Coding experts tend to use 30-40% of their time only for comprehending the already existing code. These are two entire working days every week that are wasted on going through obsolete documentation, understanding ambiguous code, and desperately searching for developers who quit months ago. On the ...
Synergy in Clicks: Harsanyi Dividends for E-Commerce
A brief overview of the math behind the Harsanyi Dividend and a real-world application in Streamlit
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The Machine Learning “Advent Calendar” Day 22: Embeddings in Excel
Understanding text embeddings through simple models and Excel
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ChatLLM Presents a Streamlined Solution to Addressing the Real Bottleneck in AI
For the last couple of years, a lot of the conversation around AI has revolved around a single, deceptively simple question: Which model is the best? But the next question was always, the best for what? The best for reasoning? Writing? Coding? Or maybe it’s the best for images, audio, or video? Tha...
What Happens When You Build an LLM Using Only 1s and 0s
An LLM that's 41× more efficient and 9× faster than today's standard models
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MCP is a key enabler into turning your LLM into an agent by providing it with tools to retrieve real-time information or perform actions.
In this deep dive we cover how MCP works, when to use it, and what to watch out for.
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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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