LLM Engineer's Handbook — Master the art of engineering Large Language Models #LLMs from concept to production: http://
amzn.to/4dUQrv6 v/ @PacktDataML Implement robust data pipelines and manage LLM training cycles Create your own LLM and refine with the help of hands-on
MACHINE LEARNING
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LLM Engineer’s Handbook for Training and Production
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Reasoning Models: The Next AI Leap Toward Inspectable Thinking
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Why Reasoning Models Are The Next Leap In AI #Reasoning models mark a critical step forward in #AI, moving systems from fluent prediction toward structured #thinking that can be inspected and trusted. Work coming out of #MBZUAI shows how open, sovereign models could shape the
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Architecting AI Software Systems: A Guide to Scalable Integration
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"Architecting AI Software Systems: Crafting robust and scalable AI systems for modern software development" at http://
amzn.to/4oMi9Ag v/ @PacktDataML 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Learn to integrate AI with traditional software architectures, enabling architects to design -
New Edition of Graph Machine Learning Book Released
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2nd Edition — now at http://
amzn.to/45Y3LyI v/ @PacktDataML Graph Machine Learning — Latest advancements in Graph Data to build robust #MachineLearning algorithms 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Master new graph ML techniques through updated examples using PyTorch Geometric and -
Resource for Developing and Debugging Machine Learning Models
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Develop and Debug high-performance, low-bias, and explainable #MachineLearning and #DeepLearning Models with #Python : http://
amzn.to/3u2JiIB by @AliMLearning via @PacktDataML —————
#DataScientist #DataScience #AI #XAI #ML #PyTorch -
Guide to Building Custom RAG Pipelines
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RAG-Driven #GenerativeAI — Build custom Retrieval Augmented Generation pipelines: http://
amzn.to/3MWnIek v/ @PacktDataML ——
#AI #MachineLearning #DataScience #GenAI #LLMs
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𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Implement RAG’s traceable outputs, linking each response to its source -
daVinci-Dev: Agent-Native Mid-Training for Software Engineering
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daVinci-Dev: Agent-native Mid-training for Software Engineering Zeng et al.: https://
arxiv.org/abs/2601.18418 #ArtificialIntelligence #DeepLearning #MachineLearning -
DreamerV2: Mastering Atari with Discrete World Models
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#PaperADay 14
2022: MASTERING ATARI WITH DISCRETE WORLD MODELS
(DreamerV2) https://danijar.com/project/dreamerv2/
… https://arxiv.org/pdf/2010.02193 DreamerV1 was mostly targeted at continuous control tasks, but it also demonstrated basic playing of Atari games and DMLab tasks. DreamerV2 improved the -
RLHF: OpenAI’s Human Feedback Training Method Explained
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Ils ont été pendant longtemps le labo d'openai, le Reinforcement Learning Human Feedback, c'était la notation qu'on nous demandais à chaque reponse
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Wisconsin CS Team Benchmarks Accepted to ICLR 2026
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Great to see benchmarks like this! Congrats to @wisconsinCS on this work and the authors on #ICLR2026 acceptance: @jiayuwang111 @ming5_alvin @DulepetRiya @LSearch123
, Austin Xu, @KeZixuan @fredsala @awsTO @CaimingXiong @JotyShafiq Always great partnering across academia and