Five Questions About Chronos-2, the Time Series Foundation Model
Part 1: A practitioner's walkthrough of univariate, multivariate, covariate-informed, and cold-start forecasting.
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EmoNet: Speaker-Aware Transformers for Emotion Recognition — and What I’d Build Differently in 2026
A retrospective on my MS thesis, the leaderboard it placed on, and the LLM shift that has reshaped the field since.
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The Infrastructure Behind Making Local LLM Agents Actually Useful
Lessons from building a fast, reliable scientific agent with local open-weight models, vLLM, and long-context infrastructure
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DiffuJudge-AV: A Diffusion-Inspired Framework for Calibrated AV Video Evaluation
A diffusion-inspired framework for stress-testing and denoising LLM-as-a-Judge pipelines, applied to safety-critical driving video.
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Learning From Pairwise Preferences: An Introduction to the Bradley Terry Model
How to Turn Simple Head-to-Head Choices Into Probabilistic Rankings
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Most AI Agents Fail in Production Because They’re Built Backwards
Good models don't save bad architecture, and most teams learn that the hard way.
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PySpark Optimization: 12 Proven Techniques to Speed Up Your Spark Jobs
Modern data pipelines handle massive volumes of structured and unstructured data every day. As datasets grow, poorly optimized Spark jobs become slower, more expensive, and harder to scale. Common issues include long execution times, excessive shuffling, memory bottlenecks, and inefficient joins. Ef...
The Statistics of Token Selection: Logits, Temperature, and Top-P Walkthrough
When large language models, or LLMs for short, produce outputs, several criteria are at stake, including not only overall response relevance but also coherence and creativity.
Visual Debugging Tools for Machine Learning Workflows
In this article, we cover three topics: what to visualize during training, the tools that provide those visualizations, and the methods to capture model computations directly using hooks and breakpoints.
How I turned 100 messy pdfs into structured insights by building a deterministic loop around agents
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The Domain Shift: Moving Data Governance from Product Triage to Infrastructure Investment
How shifting the operational focus from isolated data products to systemic domain architecture resolves technical bottlenecks and optimizes platform investment.
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10 Everyday Tasks You Can Automate with AI Today (With n8n Templates)
Most AI automation content sounds useful, but then leaves you with one big question: where to start? Instead of only talking about automation, you probably want to create real-world automation workflows with minimal coding. That’s where the power of low-code platforms like n8n comes into play. Here ...
I Built My First ETL Pipeline as a Complete Beginner. Here’s How.
A beginner's honest walkthrough of Extract, Transform, Load using the GitHub API
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From TF-IDF to Transformers: Implementing Four Generations of Semantic Search
How did semantic search evolve from simple keyword matching into modern transformer-based language understanding? This hands-on article builds four generations of semantic search systems step by step using Python.
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Implementing Hybrid Semantic-Lexical Search in RAG
Implementing hybrid search strategies is a critical step in building modern RAG (Retrieval-Augmented Generation) systems , especially when shifting from prototype to production-ready solutions.
Introducing the Agent Toolkit for Amazon Web Services
It’s like having your own personal expert AWS solutions architect and data engineer rolled into one.
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Build a Claude Cowork-Like Browser Agent Using Playwright MCP and Claude Desktop
Claude Cowork shifts AI from chat-based assistance to task delegation. Instead of giving users instructions, it performs actions directly on the user’s computer, files, applications, and browser workflows. Combined with Playwright MCP, Claude Desktop can open pages, click buttons, fill forms, extrac...