machine learning – Page 30 – Andrew Fairless, Ph.D.

What I Read: Semi-Supervised Learning

By Andrew Fairless on January 31, 2022December 12, 2021

https://lilianweng.github.io/lil-log/2021/12/05/semi-supervised-learning.html Learning with not Enough Data Part 1: Semi-Supervised LearningDec 5, 2021 by Lilian Weng “When facing a limited amount of labeled data for supervised learning tasks, four approaches areContinue readingWhat I Read: Semi-Supervised Learning

What I Learn: Meta-Learning, Keyphrase Extraction

By Andrew Fairless on January 18, 2022December 11, 2021

https://sinequa.medium.com/meta-learning-for-keyphrase-extraction-54ec960cd2ba Meta-Learning for Keyphrase ExtractionSinequaSep 6 “KeyPhrase Extraction (KPE) is the process of extracting relevant chunks of words from a document to best capture and represent its content…. we outlineContinue readingWhat I Learn: Meta-Learning, Keyphrase Extraction

What I Read: Exploring beauty of pure mathematics

By Andrew Fairless on January 12, 2022December 11, 2021

https://deepmind.com/blog/article/exploring-the-beauty-of-pure-mathematics-in-novel-ways Exploring the beauty of pure mathematics in novel ways01 Dec 2021Alex Davies, Pushmeet Kohli, Demis Hassabis “…we explored the potential of machine learning (ML) to recognize mathematical structures andContinue readingWhat I Read: Exploring beauty of pure mathematics

What I Read: Neural-Control Family

By Andrew Fairless on January 10, 2022December 11, 2021

https://www.gshi.me/blog/NeuralControl/ Neural-Control Family: What Deep Learning + Control Enables in the Real WorldGuanya Shi “…is machine learning (especially deep learning) really ready to be deployed in safety-critical systems?”

What I Read: Maps of Model Space, Stan

By Andrew Fairless on January 5, 2022December 11, 2021

https://statmodeling.stat.columbia.edu/2021/11/19/drawing-maps-of-model-space-with-modular-stan/ Drawing Maps of Model Space with Modular StanPosted on November 19, 2021 9:50 AM by AndrewThis post is by Ryan Bernstein. “What if instead of describing one model atContinue readingWhat I Read: Maps of Model Space, Stan

What I Read: AntiPatterns, MLOps

By Andrew Fairless on January 4, 2022December 11, 2021

https://arxiv.org/abs/2107.00079 Using AntiPatterns to avoid MLOps MistakesNikhil Muralidhar, Sathappah Muthiah, Patrick Butler, Manish Jain, Yu Yu, Katy Burne, Weipeng Li, David Jones, Prakash Arunachalam, Hays ‘Skip’ McCormick, Naren Ramakrishnan “HereContinue readingWhat I Read: AntiPatterns, MLOps

What I Read: Graph Neural Networks, Differential Geometry, Algebraic Topology

By Andrew Fairless on January 3, 2022December 11, 2021

https://towardsdatascience.com/graph-neural-networks-through-the-lens-of-differential-geometry-and-algebraic-topology-3a7c3c22d5f Graph Neural Networks through the lens of Differential Geometry and Algebraic TopologyMichael Bronstein “Differential geometry and algebraic topology are not encountered very frequently in mainstream machine learning… tools fromContinue readingWhat I Read: Graph Neural Networks, Differential Geometry, Algebraic Topology

What I Read: Model Ensembles Are Faster

By Andrew Fairless on December 29, 2021November 16, 2021

https://ai.googleblog.com/2021/11/model-ensembles-are-faster-than-you.html Model Ensembles Are Faster Than You ThinkWednesday, November 10, 2021Posted by Xiaofang Wang, Intern and Yair Alon (prev. Movshovitz-Attias), Software Engineer, Google Research“We demonstrate that ensembles of even aContinue readingWhat I Read: Model Ensembles Are Faster

What I Read: Improving a Machine Learning System (Part 2 – Features)

By Andrew Fairless on December 27, 2021November 16, 2021

https://danshiebler.com/2021-11-09-ml-systems-2/ Improving a Machine Learning System (Part 2 – Features)Dan ShieblerPosted on November 9, 2021 “…one of the most important parts of improving a machine learning system is improving theContinue readingWhat I Read: Improving a Machine Learning System (Part 2 – Features)

What I Read: Improving a Machine Learning System (Part 1 – Broken Abstractions)

By Andrew Fairless on December 22, 2021November 16, 2021

https://danshiebler.com/2021-11-06-ml-systems-1/ Improving a Machine Learning System (Part 1 – Broken Abstractions)Dan ShieblerPosted on November 6, 2021 “Making measurable improvements to a mature machine learning system is extremely difficult. In thisContinue readingWhat I Read: Improving a Machine Learning System (Part 1 – Broken Abstractions)

Tag: machine learning