📌 How to Maximize Claude Cowork

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-04-15 | ⏱️ Read time: 9 min read

Learn how to get the most out of Claude Cowork

#DataScience #AI #Python

📌 Beyond Prompting: Using Agent Skills in Data Science

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-04-17 | ⏱️ Read time: 7 min read

How I turned my eight-year weekly visualization habit into a reusable AI workflow

#DataScience #AI #Python

📌 You Don’t Need Many Labels to Learn

🗂 Category: MACHINE LEARNING

🕒 Date: 2026-04-17 | ⏱️ Read time: 10 min read

What if an unsupervised model could become a strong classifier with only a handful of…

#DataScience #AI #Python

📌 6 Things I Learned Building LLMs From Scratch That No Tutorial Teaches You

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-04-17 | ⏱️ Read time: 11 min read

From rank-stabilized scaling to quantization stability: A statistical and architectural deep dive into the optimizations…

#DataScience #AI #Python

📌 A Practical Guide to Memory for Autonomous LLM Agents

🗂 Category: AGENTIC AI

🕒 Date: 2026-04-17 | ⏱️ Read time: 14 min read

Architectures, pitfalls, and patterns that work

#DataScience #AI #Python

📌 AI Agents Need Their Own Desk, and Git Worktrees Give Them One

🗂 Category: AGENTIC AI

🕒 Date: 2026-04-18 | ⏱️ Read time: 20 min read

Git worktrees, parallel agentic coding sessions, and the setup tax you should be aware of

#DataScience #AI #Python

📌 How to Learn Python for Data Science Fast in 2026 (Without Wasting Time)

🗂 Category: PROGRAMMING

🕒 Date: 2026-04-18 | ⏱️ Read time: 8 min read

What I wish I did at the beginning of my journey

#DataScience #AI #Python

📌 What It Actually Takes to Run Code on 200M€ Supercomputer

🗂 Category: DISTRIBUTED COMPUTING

🕒 Date: 2026-04-16 | ⏱️ Read time: 11 min read

Inside MareNostrum V: SLURM schedulers, fat-tree topologies, and scaling pipelines across 8,000 nodes in a…

#DataScience #AI #Python

📌 Your RAG System Retrieves the Right Data — But Still Produces Wrong Answers. Here’s Why (and How to Fix It).

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-04-18 | ⏱️ Read time: 17 min read

Your RAG system is retrieving the right documents with perfect scores — yet it still…

#DataScience #AI #Python

📌 Proxy-Pointer RAG: Structure Meets Scale at 100% Accuracy with Smarter Retrieval

🗂 Category: LARGE LANGUAGE MODEL

🕒 Date: 2026-04-19 | ⏱️ Read time: 14 min read

Open source. 5-minute setup. Vector RAG done right—try it yourself.

#DataScience #AI #Python

📌 Dreaming in Cubes

🗂 Category: DEEP LEARNING

🕒 Date: 2026-04-19 | ⏱️ Read time: 10 min read

Generating Minecraft Worlds with Vector Quantized Variational Autoencoders (VQ-VAE) and Transformers

#DataScience #AI #Python

📌 KV Cache Is Eating Your VRAM. Here’s How Google Fixed It With TurboQuant.

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-04-19 | ⏱️ Read time: 11 min read

Explore the end-to-end pipeline of TurboQuant, a novel KV cache quantization framework. This overview breaks…

#DataScience #AI #Python

📌 What Does the p-value Even Mean?

🗂 Category: DATA SCIENCE

🕒 Date: 2026-04-20 | ⏱️ Read time: 7 min read

And what does it tell us?

#DataScience #AI #Python

📌 Context Payload Optimization for ICL-Based Tabular Foundation Models

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-04-20 | ⏱️ Read time: 16 min read

Conceptual overview and practical guidance

#DataScience #AI #Python

📌 The LLM Gamble

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-04-20 | ⏱️ Read time: 8 min read

Why it tickles your brain to use an LLM, and what that means for the…

#DataScience #AI #Python

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📌 From Risk to Asset: Designing a Practical Data Strategy That Actually Works

🗂 Category: DATA SCIENCE

🕒 Date: 2026-04-20 | ⏱️ Read time: 11 min read

How to turn data into a strategic asset that enables faster decisions, reduces uncertainty, and…

#DataScience #AI #Python

📌 DIY AI & ML: Solving The Multi-Armed Bandit Problem with Thompson Sampling

🗂 Category: MACHINE LEARNING

🕒 Date: 2026-04-21 | ⏱️ Read time: 17 min read

How you can build your own Thompson Sampling Algorithm object in Python and apply it…

#DataScience #AI #Python

📌 Git UNDO : How to Rewrite Git History with Confidence

🗂 Category: PROGRAMMING

🕒 Date: 2026-04-21 | ⏱️ Read time: 24 min read

For any data scientist who works in a team, being able to undo Git actions…

#DataScience #AI #Python

📌 How to Call Rust from Python

🗂 Category: PROGRAMMING

🕒 Date: 2026-04-21 | ⏱️ Read time: 10 min read

A guide to bridging the gap between ease of use and raw performance.

#DataScience #AI #Python

🔥 Google Colab has added the option of retraining 500+ open-source neural networks

Unsloth has released a convenient notebook for configuring models.

Instructions:

1. Open the page in Colab: https://colab.research.google.com/github/unslothai/unsloth/blob/main/studio/Unsloth_Studio_Colab.ipynb

2. Run the blocks and the Unsloth Studio itself.

3. Select a model and a dataset.

4. Click "Start Training" and monitor the progress in real time.

5. Everything is ready - you can immediately compare the regular and fine-tuned versions of the model in the chat.