I have this excellent new book from Manning Publications >> #MachineLearning for Tabular Data: XGBoost, Deep Learning, and #AI" by Mark Ryan & Luca Massaron Get it here: amzn.to/41J8WA6 • Master XGBoost • Apply deep learning to tabular data • Deploy models locally and in

Ever missed an AMA bc life got in the way? Good news! DataTalksClub is reading Machine Learning for Tabular Data next week, & authors, Mark Ryan & Luca Massaron, will be there to answer your questions. Details: mng.bz/9y5l Get the book: mng.bz/Wwx0

We have a new Book of the Week event starting today on DataTalksClub Slack! This week, we're featuring "Machine Learning for Tabular Data" by Mark Ryan and Luca Massaron! Ask your questions directly to the authors 👇🏼

Join us at the iconic Dôme de Paris—Porte de Versailles as our CEO Jensen Huang takes the stage for the live #GTCParis keynote at Viva Technology. Secure your pass to attend in person, or watch the livestream online for free. 📅 June 11 at 11:00 a.m. CEST 🔗Register now:

I just read this WSJ article on why Europe's tech scene is so much smaller than the US's and China's. I'm afraid that, like most articles on this topic, it largely misses the mark. Which in itself illustrates a key reason why Europe is lagging behind: when you fail to

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Continuing my series of posts on handling missing values in data science and machine learning. In this installment we talk about multivariate imputation, indicator variable technique, and domain-specific rules. (Link in the first comment.)

Link: xgblog.ai/p/dealing-with…

I have this excellent book from Manning Publications >> #MachineLearning for Tabular Data: XGBoost, Deep Learning, and #AI, by Mark Ryan & Luca Massaron Get it here: amzn.to/41J8WA6 • Master XGBoost • Apply deep learning to tabular data • Deploy models locally and in the

🔑 Unlock powerful market insights. 💸 Learn how to fine-tune Gemma 3 1B-IT for financial sentiment analysis and make more informed investment decisions. Step-by-step guide by GDE Luca Massaron → goo.gle/4feGY46

I have this excellent book from Manning Publications >> #MachineLearning for Tabular Data: XGBoost, Deep Learning, and #AI, by Mark Ryan & Luca Massaron Get it here: amzn.to/41J8WA6 • Master XGBoost • Apply deep learning to tabular data • Deploy models locally and in the

LLM adoption among US workers is closing in on 50%. Meanwhile labor productivity growth is lower than in 2020. Many counter-arguments can be made here, e.g. "they don't know yet how to be productive with it, they've only been using for 1-2 years", "50% is still too low to see

By the way, I don't know if people realize this, but the 2020 work-from-home switch coincided with a major productivity boom, and the late 2021 and 2022 back-to-office reversal coincided with a noticeable productivity drop. It's right there in the statistics. Narrative

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This is awesome! As suspected, you can do ANYTHING with XGBoost (and other GBMs) that you can do with MLPs. They are a bit tricky to setup just right out of the box, since they were not designed with all these other use cases in mind, but definitely doable. Bojan Tunguz