Data Mining and Knowledge Discovery has published my article, "Critical node identification through triplet node influence in complex networks," online. A full-text access to a view-only version of the paper by using the following link:
https://t.co/MOCzYkBbYi
This is the best 1 hour on graph engineering ever recorded, just released by Google how to go from a single agent to a full 24/7 system from scratch:
00:00 - what graphs actually are
09:16 - your first working agent
21:15 - graph engineering explained
41:03 - graph engineering in practice
52:21 - graphs that improve themselves
I've seen $500 courses that teach less than this video alone.
Watch it, then take it further with my step-by-step guide on graph engineering below.
INSTEAD OF WATCHING NETFLIX TONIGHT.
Spend 1 hour with this.
Claude AI FULL COURSE that teaches you how to BUILD and AUTOMATE anything.
The people who watch this tonight will wake up tomorrow with a new skill.
Watch it and Bookmark it now
Claude Code team just dropped a free course on loop engineering with Fable 5:
00:00 - how Claude Code works under the hood
05:01 - the agentic loop explained
16:21 - building agents with Fable 5
19:01 - why voice beats typing
32:34 - how to deploy agents with Fable 5
58:39 - Fable 5 for non-code work
this 30-minute watch will replace 10 paid courses about prompting Claude.
Bookmark this and read the article below.
🥇 1st Place Secrets: XGBoost Tips from 5x Kaggle Grandmaster Chris Deotte
Want to climb the @Kaggle leaderboards? Our own @cdeotte shared his master list of XGBoost Tips and Tricks to help you build faster, more accurate models.
The Winning Formula:
⚡ GPU-Accelerated: Set device="cuda" for massive speedups in training and iteration.
📊 Native Categoricals: Use enable_categorical=True to boost accuracy without the encoding headache.
🛠️ Feature Engineering: Create interaction features that reveal hidden data patterns.
📉 Memory Efficiency: Scale your models by optimizing data types for GPU VRAM.
Whether you're chasing Kaggle Gold or optimizing production ML, these insights from the world’s top-ranked data scientist are essential.
➡️ Read the guide: https://t.co/N6EGxSMiOO 🙌
Perplexity AI is a free research assistant.
But most academics use it like amateurs.
Here are 10 prompts to get better results (bookmark this for later):
LLMs are limited by their training data – so if you want real-time info, you need RAG.
Using Retrieval-Augmented Generation gives your models access to all sorts of helpful data.
In this course, @ania_kubow helps you build your own RAG chatbot with JS.
https://t.co/XcV4eZ7WVP
Computational Design of Potentially Multifunctional Antimicrobial Peptide Candidates via a Hybrid Generative Model https://t.co/udciUSkEq4 #mdpiijms via @IJMS_MDPI
Gemini 2.5 Pro is the most powerful AI model in the world.
Most people don't know how to use it properly.
I have been using it to build apps, make viral content, automate my tedious tasks like research, and more.
Here are 5 ways to unlock its full power:
My new article for identifying critical nodes in complex networks has been published: Identifying Hubs Through Influential Nodes in Transportation Network by Using a Gravity Centrality Approach https://t.co/djvnISj4ZM #mdpialgorithms via @Algorithms_MDPI@MDPIOpenAccess