📌 How AI Can Become Your Personal Language Tutor

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-01-12 | ⏱️ Read time: 11 min read

How I used n8n to build AI study partners for learning Mandarin: vocabulary, listening, and…

#DataScience #AI #Python

📌 Why 90% Accuracy in Text-to-SQL is 100% Useless

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-01-12 | ⏱️ Read time: 9 min read

The eternal promise of self-service analytics

#DataScience #AI #Python

📌 When Does Adding Fancy RAG Features Work?

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-01-12 | ⏱️ Read time: 23 min read

Looking at the performance of different pipelines

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📌 Optimizing Data Transfer in Batched AI/ML Inference Workloads

🗂 Category: DATA ENGINEERING

🕒 Date: 2026-01-12 | ⏱️ Read time: 13 min read

A deep dive on data transfer bottlenecks, their identification, and their resolution with the help…

#DataScience #AI #Python

📌 Why Your ML Model Works in Training But Fails in Production

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-01-13 | ⏱️ Read time: 8 min read

Hard lessons from building production ML systems where data leaks, defaults lie, populations shift, and…

#DataScience #AI #Python

📌 How to Maximize Claude Code Effectiveness

🗂 Category: AGENTIC AI

🕒 Date: 2026-01-13 | ⏱️ Read time: 9 min read

Learn how to get the most out of agentic coding

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📌 An introduction to AWS Bedrock

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-01-13 | ⏱️ Read time: 13 min read

The how, why, what and where of Amazon’s LLM access layer

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📌 From ‘Dataslows’ to Dataflows: The Gen2 Performance Revolution in Microsoft Fabric

🗂 Category: DATA ENGINEERING

🕒 Date: 2026-01-13 | ⏱️ Read time: 8 min read

Dataflows were (rightly?) considered “the slowest and least performant option” for ingesting data into Power…

#DataScience #AI #Python