| A Practical Introduction to pymdp: A Two-Part Guide to Active Inference in Python |
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| ACCESS HPC Workshop Series |
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| Active inference textbook |
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| ActiveInference.jl: A Julia Package for Computational Modeling |
Code |
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| AI for improved HPC research - Cursor and Termius - Powerpoint |
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| An Introduction to the Julia Programming Language |
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| Attention, Transformers, and LLMs: a hands-on introduction in Pytorch |
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| Automated Machine Learning Book |
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| Data Imputation Methods for Climate Data and Mortality Data |
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| Framework to help in scaling Machine Learning/Deep Learning/AI/NLP Models to Web Application level |
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| GPU Acceleration in Python |
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| Harnessing the Power of Cloud and Machine Learning for Climate and Ocean Advances |
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| Implementing Markov Processes with Julia |
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| InsideHPC |
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| Intro to Machine Learning on HPC |
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| Intro to Statistical Computing with Stan |
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| Introduction to Deep Learning in Pytorch |
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| Introduction to Probabilistic Graphical Models |
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| Leveraging AI in Generative Assets and Environments for Play: Insights from the English Department's Digital Media Lab |
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| Machine Learning in Astrophysics |
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Learning |
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| Neural Networks in Julia |
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| Online Bachelor's in Data Science Program Guide - TechGuide |
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| Practical Machine Learning with Python |
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| PYMDP: The Official Documentation |
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| Useful R Packages for Data Science and Statistics |
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