Curious to learn about the Message Passing Neural Network (MPNN) architecture and its role in graph neural networks more broadly? Don't miss Giuseppe Futia's well-illustrated deep dive. buff.ly/4gfuF7W

Learn how to create an advanced spider chart in Python — Zvonimir Boban provides a detailed, step-by-step explanation of the entire process. buff.ly/3zjCCYS

How to Train a Vision Transformer (ViT) from Scratch by François Porcher in Towards Data Science towardsdatascience.com/how-to-train-a…

In a new hands-on tutorial, James Wilkins explains how we can leverage K-means clustering for image segmentation, and walks us through the entire implementation in Python. buff.ly/3XcBfmN

Are the reasoning capabilities of current OpenAI LLMs good enough to play a classic guessing game? Krzysztof K. Zdeb shares insights based on his experiments with playing forehead detective with several GPT models. buff.ly/4dNPoOv

How to Create a Custom Matplotlib Theme and Make Your Charts Go from Boring to Amazing | By Dario Radečić buff.ly/3ATtY3R #Matplotlib #Data #Visualization

How to Construct a Multipage Data Science Web App in Python with Taipy.io | By Alan Jones buff.ly/3Mz4gnT #Python #Data #Frameworks

What's the best way for a data science manager to organize their weekly schedule? Jose Parreño digs deep into his own process and the changes he's implemented to become more efficient and flexible. buff.ly/4gdauY2

5 Tips To Make Your Resume *Really* Stand Out in FAANG Applications - How to Make Recruiters Say ‘WOW!’ in Just 6 Seconds by Khouloud El Alami buff.ly/3X6uvad

An Introduction to Bayesian A/B Testing | By Laurin Brechter buff.ly/3ATUCtz #AI #ABTesting #Data

"We’ll start by breaking down the problem, then jump into the details of it’s Mixed Integer Programming (MIP) formulation. After that, we’ll bring in a sample dataset and solve it step by step." by Luis Fernando PÉREZ ARMAS, Ph.D. buff.ly/4cJWfHm

"In this article, I will explain and visualize the sampling strategies that define the output behavior of LLMs." How to Improve LLM Responses With Better Sampling Parameters by Dr. Leon Eversberg buff.ly/4e6XT6T

"In this article, we will use the API to obtain the subway routes located in Hamburg. Using these routes, we will create a NetworkX graph, which we will later on visualize using an interactive visualization in Folium." by Amanda Iglesias Moreno buff.ly/4dJZPCA

Using Generative AI To Get Insights From Disorderly Data Best practices for using Large Language Models to extract actionable insights even with poor metadata 🖋️ by Omer Ansari buff.ly/3z5keD1

Why Personalization Programs Fail - Hard Truths and Paths Forward by Ian Xiao buff.ly/3XdOeEH

"Structured outputs are a way of enforcing the output of an LLM to follow a pre-defined schema — usually a JSON schema." Diving Deeper with Structured Outputs by Armin Catovic buff.ly/47tO4hz

In this tutorial, Heiko Hotz dives into Automated Prompt Engineering and explores: - How it works in principle - What strategies can be used to generate prompts Then transition into a hands-on tutorial to write an Automated Prompt Engineering program from scratch!

Have you considered becoming a reviewer for papers on machine learning and adjacent fields? Shrey Pareek shares insights on what this work entails and why you might consider becoming a reviewer even if you're not an active researcher. buff.ly/47fWYir

When working with time-series data, it's often crucial to detect structural changes accurately and efficiently. Vitor Cerqueira shows how to go about it in his latest hands-on Python tutorial. buff.ly/3Mv0aNH

If you're taking your first steps in reinforcement learning, don't miss Oliver S's ongoing series on the topic — the latest installment provides an accessible introduction to Monte Carlo methods and their role in problem-solving scenarios. buff.ly/3XgEsBI