Here is my editorial endorsement: This book perfectly reflects its title "50 ML Projects to Understand LLMs". The entire book consists of exactly that: 50 projects, with tasks and subtasks pleasantly outlined, explained, and presented in a beautifully instructive and consistent
AI
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AI-Enabled Cyberattacks vs. Security Community Techniques: An Analysis
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How well do the security community's techniques hold up against AI-enabled cyberattacks? We examined 832 malicious accounts and mapped their activity onto a longstanding database of tactics and techniques used by threat actors. Here's what we learned:
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Gemma 4 hits 150M+ downloads with new, powerful 12B model for local use
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Celebrating the milestone of a massive 150+ million downloads of Gemma 4 with the release of the new Gemma 4 12B model! It's incredibly powerful for such a small model and it’s tiny enough to run locally on a laptop with just 16GB VRAM. Apache 2.0 license – happy building!
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Simpler approach in Unified Embedding Decoder Architecture category
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Conceptually, it fits nicely into the Unified Embedding Decoder Architecture category that I wrote about a while back: https://
magazine.sebastianraschka.com/p/understandin
g-multimodal-llms
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I think it's the refreshingly simple(r) approach of the two. -
Book: Machine Learning for Tabular Data by Mark Ryan and Luca Massaron
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Excellent book from @ManningBooks >> "Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI," by @MarkRyanMkm & @lucamassaron Get it here: https://
amzn.to/41J8WA6 • Master XGBoost
• Apply deep learning to tabular data
• Deploy models locally and in the cloud
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16GB VRAM Doable for Standard Hardware Except Long Context Tasks
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Maybe for very long context agent tasks, but otherwise, 16GB VRAM is pretty doable on standard hardware
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AI Programming with Python: From Zero to Hero covering ML and DL
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AI Programming with Python — From Zero to Hero: https://
amzn.to/43TkNea Thorough introductions to #AI, #MachineLearning, and #DeepLearning Hands-on introductions to #Python Discussions of supervised and unsupervised learning Explorations of classification and -
Data Without Labels: Unsupervised Machine Learning Fundamentals and Data Cleaning
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Data Without Labels — Models and Algorithms for Practical Unsupervised #MachineLearning: https://
amzn.to/4q5bbYz 𝓦𝓱𝓪𝓽 𝓨𝓸𝓾 𝓦𝓲𝓵𝓵 𝓛𝓮𝓪𝓻𝓷: Fundamental building blocks and concepts of machine learning and unsupervised learning
Data cleaning for structured and -
Gemma 4 12B released, runs comfortably on 16GB VRAM for LFM newcomers
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They should all run comfortably (if you have ~16 GB VRAM). I am quite new to LFM's, and Gemma 4 12B just came out today, so time will tell…
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AI-Powered Qualitative Data Analysis with ChatGPT and QualCoder
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Qualitative Data Analysis with ChatGPT and QualCoder: A Step-By-Step Guide to AI-Powered Coding and Thematic Analysis AI-Powered Research Toolkit — Mastering Research Series — available at https://
amzn.to/4bRsV3q