Depends, theoretical math for deep diving into research, intuition of all the topics for development and building models
MACHINE LEARNING
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Herding Algorithms and Human Intelligence in AI Systems
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One more argument: We could easily replace the sampling of the multinomial by a dynamical system, eg by herding https://
icml.cc/Conferences/20
09/papers/447.pdf
… I’m not sure randomness is needed. More on the opinion side of things: I don’t think humans are very far from being parrots. We may yet -
Andrew Ng’s Career Advice: Reading Research Papers Effectively
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This blog summarizes the career advice/reading research papers lecture in the CS230 Deep learning course by Stanford University on YouTube, and includes advice from Andrew Ng on how to read research papers. https://
kdnuggets.com/2019/09/advice
-building-machine-learning-career-research-papers-andrew-ng.html
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Good stuff never ages. -
Productionizing Machine Learning: Pipeline, Inference and Workflow Challenges
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Productionizing machine learning is the hack of a task. It can be extremely complicated, from the model pipeline to inferences and automating workflows across multiple servers. chasing some bits of it lately
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Subscribe to Weekly AI Engineering Tutorials on ML and LLMs
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If you're interested in ML, LLMs, and AI Agents and want to receive tutorials every week, subscribe to AI Engineering (for free):
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Silent Bugs: The Deep Learning Horror of Misconfigured Parameters
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Deep Learning horror genre That fear of a kwarg that isn’t set right, not erroring, only silently making your results slightly worse.
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Deep Learning Accessibility Prediction: A Decade Later Review
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Just came across this old GigaOM article. I guessed in 2013 it might take ~10 years until "packages like word2vec can make deep learning even for relatively unsophisticated users". Not bad, I think! 😀 https://
web.archive.org/web/2022070705
2644/https://old.gigaom.com/2013/08/16/were-on-the-cusp-of-deep-learning-for-the-masses-you-can-thank-google-later/
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AI Agents vs Agentic AI: Conceptual Taxonomy and Applications
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AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges Sapkota et al.: https://
arxiv.org/abs/2505.10468 #ArtificialInteligence #DeepLearning #MachineLearning -
Top Mathematics Books for Data Science and Analytics
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Top #Books on #Mathematics to Read! #BigData #Analytics #DataScience #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode https://
geni.us/Math-for-DSci
