📌 Learning, Hacking, and Shipping ML

🗂 Category: AUTHOR SPOTLIGHTS

🕒 Date: 2025-12-01 | ⏱️ Read time: 11 min read

Explore the ML lifecycle with Vyacheslav Efimov as he shares key insights for tech professionals. This discussion covers everything from creating effective data science roadmaps and succeeding in AI hackathons to the practicalities of shipping ML products. Learn how the evolution of AI is meaningfully changing the day-to-day workflows and challenges for machine learning practitioners in the field.

#MachineLearning #AI #DataScience #MLOps #Hackathon

📌 Why AI Alignment Starts With Better Evaluation

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2025-12-01 | ⏱️ Read time: 16 min read

Achieving true AI alignment is fundamentally dependent on robust evaluation. To ensure AI systems operate according to human values and intentions, we must first develop sophisticated methods to measure their behavior, test for potential risks, and identify misalignments. This goes beyond standard performance benchmarks, requiring a deeper focus on creating comprehensive testing frameworks. Without the ability to accurately assess a model's alignment, any attempt to steer it becomes guesswork, highlighting why better evaluation is the critical first step toward building safer and more reliable AI.

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📌 How to Generate QR Codes in Python

🗂 Category: PROGRAMMING

🕒 Date: 2025-12-02 | ⏱️ Read time: 7 min read

Unlock the ability to generate QR codes with Python. This beginner-friendly tutorial provides a step-by-step guide to using the popular "qrcode" package. Learn how to easily create and customize QR codes for your applications, from encoding URLs to embedding custom data.

#Python #QRCode #Programming #PythonTutorial

📌 The Machine Learning Lessons I’ve Learned This Month

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-01 | ⏱️ Read time: 4 min read

Discover key machine learning lessons from recent hands-on experience. This monthly review covers the real-world costs and trade-offs of using AI assistants like Copilot, the critical importance of intentionality in project choices (as even a non-choice has consequences), and an exploration of finding unexpected "Christmas connections" within data. A concise look at practical, hard-won insights for ML practitioners.

#MachineLearning #Copilot #AIStrategy #DataScience

📌 The Machine Learning “Advent Calendar” Day 1: k-NN Regressor in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-01 | ⏱️ Read time: 16 min read

Kick off a Machine Learning Advent Calendar series with a practical guide to the k-NN regressor. This first installment demonstrates how to implement this fundamental, distance-based model using only Microsoft Excel. It's a great hands-on approach for understanding core ML concepts from scratch, without the need for a complex coding environment.

#MachineLearning #kNN #Excel #DataScience #Regression

📌 The Machine Learning “Advent Calendar” Day 2: k-NN Classifier in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-02 | ⏱️ Read time: 9 min read

Discover how to implement the k-Nearest Neighbors (k-NN) classifier directly in Excel. This article, part of a Machine Learning "Advent Calendar" series, explores the popular classification algorithm along with its variants and improvements. It offers a practical, hands-on approach to understanding a fundamental ML concept within a familiar spreadsheet environment, making it accessible even without a dedicated coding setup.

#MachineLearning #kNN #Excel #DataScience

📌 JSON Parsing for Large Payloads: Balancing Speed, Memory, and Scalability

🗂 Category: DATA ENGINEERING

🕒 Date: 2025-12-02 | ⏱️ Read time: 12 min read

When processing large JSON payloads, the choice of a parsing library is critical for system performance. This benchmark analysis explores the trade-offs between various libraries, focusing on key metrics like parsing speed, memory consumption, and overall scalability. Discover which tools offer the optimal balance for high-volume data scenarios, helping you make informed decisions for building efficient and resilient applications.

#JSON #Performance #Benchmarking #DataEngineering #Backend

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📌 The Architecture Behind Web Search in AI Chatbots

🗂 Category: LLM APPLICATIONS

🕒 Date: 2025-12-04 | ⏱️ Read time: 16 min read

Explore the technical architecture powering web search in AI chatbots. This analysis breaks down how generative models retrieve and integrate live web data to provide current answers, highlighting the crucial shift towards Generative Engine Optimization (GEO). Learn what this new paradigm means for content visibility in an AI-first search landscape, moving beyond traditional SEO.

#AI #GEO #Chatbots #Search #RAG

📌 Overcoming the Hidden Performance Traps of Variable-Shaped Tensors: Efficient Data Sampling in PyTorch

🗂 Category: DEEP LEARNING

🕒 Date: 2025-12-03 | ⏱️ Read time: 10 min read

Unlock peak PyTorch performance by addressing the hidden bottlenecks caused by variable-shaped tensors. This deep dive focuses on the critical data sampling phase, offering practical optimization strategies to handle tensors of varying sizes efficiently. Learn how to analyze and improve your data loading pipeline for faster model training and overall performance gains.

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📌 The Machine Learning “Advent Calendar” Day 3: GNB, LDA and QDA in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-03 | ⏱️ Read time: 10 min read

Day 3 of the Machine Learning "Advent Calendar" series explores Gaussian Naive Bayes (GNB), Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis (QDA). This guide uniquely demonstrates how to implement these powerful classification algorithms directly within Excel, offering a practical, code-free approach. Learn the core concepts behind these models, transitioning from simple local distance metrics to a more robust global probability framework, making advanced statistical methods accessible to a wider audience.

#MachineLearning #Excel #DataScience #LDA #Statistics

📌 How to Turn Your LLM Prototype into a Production-Ready System

🗂 Category: LLM APPLICATIONS

🕒 Date: 2025-12-03 | ⏱️ Read time: 15 min read

Transforming a promising LLM prototype into a production-ready system involves significant engineering challenges. This guide outlines the essential steps and best practices for moving beyond the experimental phase, focusing on building scalable, reliable, and efficient LLM applications for real-world deployment. Learn how to successfully operationalize your language model from concept to production.

#LLM #MLOps #ProductionAI #LLMOps

📌 Multi-Agent Arena: Insights from London Great Agent Hack 2025

🗂 Category: AGENTIC AI

🕒 Date: 2025-12-03 | ⏱️ Read time: 16 min read

Key insights from the London Great Agent Hack 2025 reveal critical success factors for multi-agent systems. The focus has shifted towards building highly robust agents capable of withstanding adversarial testing and unexpected scenarios. A major theme was the importance of "glass-box reasoning"—making agent decision-making transparent and interpretable. Ultimately, red-team resilience and explainability, not just raw performance, were the defining characteristics of the top-performing solutions.

#MultiAgentSystems #AIAgents #ExplainableAI #AISecurity

📌 How to Code Your Own Website with AI

🗂 Category: AGENTIC AI

🕒 Date: 2025-12-03 | ⏱️ Read time: 8 min read

Unlock the potential of AI in web development. This guide explains how to "vibe-code" a website, a modern method where AI tools translate your high-level design concepts and desired feel directly into functional code. Learn a more intuitive and streamlined approach to building websites from scratch.

#AI #WebDevelopment #AICoding #DeveloperTools #GenerativeAI

📌 How to Use Simple Data Contracts in Python for Data Scientists

🗂 Category: DATA SCIENCE

🕒 Date: 2025-12-02 | ⏱️ Read time: 5 min read

Prevent your data pipelines from breaking unexpectedly. This article demonstrates how to implement simple data contracts in Python using Pandera, an open-source validation library. Learn to define and enforce data quality rules to build more robust and reliable data science workflows, ensuring your data meets expectations before it causes issues downstream.

#DataContracts #Python #DataScience #Pandera #DataValidation

📌 The Step-by-Step Process of Adding a New Feature to My IOS App with Cursor

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-12-05 | ⏱️ Read time: 6 min read

This article provides a step-by-step walkthrough of adding a new feature to an iOS app using the AI-powered editor, Cursor. It offers practical insights for developers, highlighting how Cursor excels at code generation but is less effective for UI/UX design tasks. This guide demonstrates a real-world workflow for integrating AI coding assistants into the development process, showcasing both their strengths and limitations.

#iOSDev #AICoding #AppDevelopment #Cursor

📌 The Machine Learning “Advent Calendar” Day 5: GMM in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-05 | ⏱️ Read time: 6 min read

Explore Gaussian Mixture Models (GMM), a powerful clustering algorithm that serves as a natural extension and improvement over k-Means. This guide, part of a Machine Learning Advent Calendar series, uniquely demonstrates how to implement and understand GMMs entirely within Microsoft Excel. It's a practical approach for grasping core ML concepts without requiring a dedicated coding environment, making advanced data science techniques more accessible.

#MachineLearning #GMM #Excel #DataScience #Clustering