kdn practical sql tricks

Practical SQL Tricks Every Data Scientist Should Know

  Contents# Introduction# Setting Up the Dataset# 1. Measuring Time Between Events with LAG()# 2. Comparing a Row to Other Rows in the Same Table with a Self-Join# 3. Selecting the Top Row per Group with ROW_NUMBER()# 4. Segmenting Customers by Spend with NTILE(n)# 5. Smoothing Noisy Data with a Rolling Window# 6. Aggregating Conditionally with FILTER# 7. Detecting Consecutive Activity Streaks with Window …

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7 Crucial Barriers Between Data Teams and Self-Healing Data Architecture

ContentsIntroductionBarrier 1 | Context and failure recallBarrier 2 | Elastic infrastructureBarrier 3 | Operational Agents and Quality DataBarrier 4 | Git for DataBarrier 5 | Pervasion through the industryBarrier 6 | Agent Sandboxes and New OrchestratorsBarrier 7 | Standards for Proxy Servers and Agent DefinitionPutting it all together | A Single Pane of Glass for AI Introduction , AI examples …

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Noob Series Loss Function Explained 1

Loss Function Explained For Noobs (How Models Know They Are Wrong)

  Contents# Introduction# What Is a Loss Function?# Mean Squared Error# Mean Absolute Error# Cross-Entropy Loss# Loss vs. Accuracy# The Training Loop# Final Thoughts # Introduction  I know that when beginners start learning machine learning, things seem easy at first. You follow a tutorial that asks you to load a dataset, train a model, and then you see something like this: loss = “mse” …

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kdn the roadmap to becoming an llm engineer in 2026 feature

The Roadmap to Becoming an LLM Engineer in 2026

  Contents# Introduction# Step 1: Building the Foundation# Step 2: Designing Prompts and Building Tool-Calling Systems# Step 3: Building Retrieval Systems Beyond the Basics# Step 4: Fine-Tuning and Aligning Models# Step 5: Serving and Operating LLM Applications# Recommended Learning Resources# Final Thoughts # Introduction  An LLM engineer is not the same thing as a general machine learning engineer. Where a machine learning engineer might …

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KDN Shittu Pairing Claude Code with Local Models

Pairing Claude Code with Local Models

    Contents# Introduction# How Claude Code Connects to Any Local Model# Backend 1: Ollama# Backend 2: LM Studio# Backend 3: llama.cpp# The Complete settings.json# Best Local Models for Claude Code in 2026# Troubleshooting Common Issues# Conclusion # Introduction  Agentic coding sessions are expensive. A single Claude Code session — reading files, writing code, running tests, iterating — can burn 10–50x more tokens than a …

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Diffusion Gemma Social.width 1300

Introducing DiffusionGemma

ContentsWhy diffusion for text?The trade-off with traditional models Why diffusion for text? While the AI research community has explored diffusion-based text generation for years, applying it to large models has remained a challenge. DiffusionGemma changes this by shifting how models use hardware. The trade-off with traditional models Most language models act like a typewriter, generating …

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