Probabilistic #MachineLearning — An INTRODUCTION (2nd Ed. 2022, 858-page PDF): http://
bit.ly/3seAc5G by @sirbayes Get the print copy: https://
amzn.to/48broB3
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#AI #DeepLearning #BigData #DataScience #Mathematics #Probability #Statistics #LinearAlgebra #NeuralNetworks
RESEARCH
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Probabilistic Machine Learning Introduction 2nd Edition PDF Guide
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Introduction to Statistical Learning Textbook Revised and Updated
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Brilliant classic textbook, revised and updated — Introduction to Statistical Learning, with Applications in R: http://
amzn.to/3mpECFT
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#BigData #DataScience #AI #MachineLearning #StatisticalLearning #Statistics #Mathematics #Algorithms #Rstats #Coding #DataScientists -
Directed Acyclic Graphs for Causal Inference Tutorial
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Tutorial — Using directed acyclic graphs to model & test causal hypotheses: https://
keithmcnulty.github.io/causal_inferen
ce_intro/#1
… …based on "Statistical Rethinking: A Bayesian Course with Examples" http://
amzn.to/49FLp4d
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#Statistics #DataScience #Mathematics #ORMS #MachineLearning #AI #Rstats #Causality -
SAS Innovate 2024: Leading AI Data Analytics Conference in Las Vegas
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SAS Innovate is April 16-19 at ARIA Resort & Casino in Las Vegas. Register now to join this leading #AI / Data / #Analytics experience of 2024: https://
sas.com/gms/redirect.j
sp?detail=PLN22951_174944999
… by @SASsoftware ————
#SASInnovate #DataScience #ML #SASVisionary #ad #DecisionScience -
Claude 3 and Gemini 1.5 Pro Release Sparks Shared Ideas
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This is awesome, Andrew! I feel like we all had the same idea after Claude 3 and Gemini 1.5 Pro dropped lol
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SAS Innovate 2024: AI and Analytics Conference in Las Vegas
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#DataScience #MachineLearning #DecisionScience #SASVisionary #ad Go all in on #AI and Analytics at #SASInnovate 2024, by @SASsoftware in Las Vegas on April 16-19. Register at: https://
sas.com/gms/redirect.j
sp?detail=PLN22951_174944999
… It’s all under one roof and all at SAS Innovate. Whether you are a company -
RAG and Prompt Engineering: Preferred Over Fine-Tuning
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If you’re still wondering when to apply either RAG vs fine-tuning, we have a simple answer – always try RAG + prompt engineering first! Fine-tuning only makes sense when you have a domain specific task and doesn’t always result in performant solutions. Additionally, it takes a
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Meta’s 24k H100 Cluster Pods Infrastructure for Llama3
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Here's details on Meta's 24k H100 Cluster Pods that we use for Llama3 training.
* Network: two versions RoCEv2 or Infiniband. * Llama3 trains on RoCEv2
* Storage: NFS/FUSE based on Tectonic/Hammerspace
* Stock PyTorch: no real modifications that aren't upstreamed
* NCCL with -
Scaling Learning Rate with Batch Size in Model Training
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I think it really depends on the batch size you are using. Let's say you are multiplying the batch size by x, then you should multiply the learning rate by sqrt(x)
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HRI Conference Workshop on Embodied Voices and TTS Models
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Audience question on character voices and TTS needs @HRI_Conference – Consider our newly accepted RSS Workshop on Embodied Voices on July 15! Bringing the latest deep TTS models together with roboticists https://
rosielab.github.io/wev/ #hri2024