Andrew Fairless – Page 51 – Andrew Fairless, Ph.D.

What I Read: Autonomous Building of Composable Models

By Andrew Fairless on December 1, 2021November 16, 2021

https://thegradient.pub/strong-ai-requires-autonomous-building-of-composable-models/ Strong AI Requires Autonomous Building of Composable Models30.Oct.2021Jonathan MuganDr. Jonathan Mugan is a principal scientist at DeUmbra and is the author of The Curiosity Cycle. “…AI must be ableContinue readingWhat I Read: Autonomous Building of Composable Models

What I Read: Limits Discovered in Quest for Optimal Solutions

By Andrew Fairless on December 1, 2021November 16, 2021

https://www.quantamagazine.org/surprising-limits-discovered-in-quest-for-optimal-solutions-20211101/ Surprising Limits Discovered in Quest for Optimal SolutionsMax G. LevyContributing WriterNovember 1, 2021 “Algorithms that zero in on solutions to optimization problems are the beating heart of machine reasoning.Continue readingWhat I Read: Limits Discovered in Quest for Optimal Solutions

What I Read: How to assign partial credit on an exam of true-false questions

By Andrew Fairless on November 30, 2021November 16, 2021

https://terrytao.wordpress.com/2016/06/01/how-to-assign-partial-credit-on-an-exam-of-true-false-questions/ How to assign partial credit on an exam of true-false questions?By Terence Tao1 June, 2016Updates on my research and expository papers, discussion of open problems, and other maths-related topics.Continue readingWhat I Read: How to assign partial credit on an exam of true-false questions

What I Read: machine learning with differential privacy

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

https://differentialprivacy.org/how-to-deploy-ml-with-dp/ How to deploy machine learning with differential privacy?Posted by Nicolas Papernot and Abhradeep Thakurta on October 25, 2021. “In many applications of machine learning, such as machine learning forContinue readingWhat I Read: machine learning with differential privacy

What I Read: A Behind-the-Scenes Look at How Postman’s Data Team Works

By Andrew Fairless on November 23, 2021November 16, 2021

https://humansofdata.atlan.com/2021/10/a-behind-the-scenes-look-at-how-postmans-data-team-works/ A Behind-the-Scenes Look at How Postman’s Data Team WorksOctober 7, 2021Prukalpa Sankar “But after a lot of effort to build better infrastructure and processes, Postman’s data team is nowContinue readingWhat I Read: A Behind-the-Scenes Look at How Postman’s Data Team Works

What I Read: Is the data engineer still the “worst seat at the table?”

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

https://towardsdatascience.com/the-future-of-the-data-engineer-4dcfa53800ab?gi=f71612388916 The Future of the Data EngineerIs the data engineer still the “worst seat at the table?” Thoughts on the past, present, and future of tooling, processes, and culture inContinue readingWhat I Read: Is the data engineer still the “worst seat at the table?”

What I Read: Machine learning is just statistics + quantifier reversal

By Andrew Fairless on November 18, 2021November 16, 2021

https://jeremybernste.in/writing/ml-is-just-statistics Machine learning is just statistics + quantifier reversaljeremybernsteLos Angeles, 21 Oct 2021 “But in machine learning there’s a switcheroo—we select the sample of data first, and then we useContinue readingWhat I Read: Machine learning is just statistics + quantifier reversal

What I Read: First-Principles Theory of Neural Network Generalization

By Andrew Fairless on November 17, 2021November 16, 2021

https://natluk.net/a-first-principles-theory-of-neuralnetwork-generalization-the-berkeley-artificial-intelligence-research-blog/ A First-Principles Theory of Neural Network Generalization – The Berkeley Artificial Intelligence Research BlogNatLuk Community25 October 2021 “Perhaps the greatest of these mysteries has been the question of generalization:Continue readingWhat I Read: First-Principles Theory of Neural Network Generalization

What I Read: Deciding Which Tasks Should Train Together

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

https://ai.googleblog.com/2021/10/deciding-which-tasks-should-train.html Deciding Which Tasks Should Train Together in Multi-Task Neural NetworksMonday, October 25, 2021Posted by Christopher Fifty, Research Engineer, Google Research, Brain Team “…there may be instances when learning fromContinue readingWhat I Read: Deciding Which Tasks Should Train Together

What I Read: Introduction AutoEncoder

By Andrew Fairless on November 15, 2021October 24, 2021

https://www.theaidream.com/post/an-introduction-to-autoencoder-and-variational-autoencoder-vae Introduction to AutoEncoder and Variational AutoEncoder(VAE)Nagesh Singh ChauhanJul 28“In recent years, deep learning-based generative models have gained more and more interest…. we will dive deep into these generative networksContinue readingWhat I Read: Introduction AutoEncoder

Author: Andrew Fairless