Andrew Fairless – Page 82 – Andrew Fairless, Ph.D.

What I Read: Common Sense Computers

By Andrew Fairless on December 23, 2020December 10, 2020

https://www.quantamagazine.org/common-sense-comes-to-computers-20200430/ artificial intelligenceCommon Sense Comes Closer to ComputersThe problem of common-sense reasoning has plagued the field of artificial intelligence for over 50 years. Now a new approach, borrowing from twoContinue readingWhat I Read: Common Sense Computers

What I Read: DevOps for ML Data

By Andrew Fairless on December 23, 2020December 10, 2020

https://tecton.ai/blog/devops-ml-data/ Why We Need DevOps for ML DataPosted by Kevin Stumpf on April 28, 2020 “Unfortunately, most tools under the MLOps banner tend to focus only on workflows around theContinue readingWhat I Read: DevOps for ML Data

What I Read: Tonks Multi-Task Model

By Andrew Fairless on December 22, 2020December 10, 2020

https://medium.com/shoprunner/tonks-building-one-multi-task-model-to-rule-them-all-3e5d020f1f2b Tonks: Building One (Multi-Task) Model to Rule Them All!Co-written by Nicole Carlson and Michael SugimuraMichael SugimuraApr 28 “Tonks is a library that streamlines the training of multi-task PyTorch networks.Continue readingWhat I Read: Tonks Multi-Task Model

What I Read: Coding habits for data scientists

By Andrew Fairless on December 22, 2020December 9, 2020

https://www.thoughtworks.com/insights/blog/coding-habits-data-scientists 21 Oct 2019Coding habits for data scientistsDavid TanDeveloper “If you’ve tried your hand at machine learning or data science, you know that code can get messy, quickly…. While thisContinue readingWhat I Read: Coding habits for data scientists

What I Read: Developers Databases

By Andrew Fairless on December 21, 2020December 9, 2020

https://medium.com/@rakyll/things-i-wished-more-developers-knew-about-databases-2d0178464f78 Things I Wished More Developers Knew About DatabasesJaana B. DoganApr 21 “In data-heavy systems, databases are at the core of system design goals and tradeoffs…. I’m sharing a fewContinue readingWhat I Read: Developers Databases

What I Read: Peer Reviewing Data Science Projects

By Andrew Fairless on December 21, 2020December 9, 2020

https://towardsdatascience.com/peer-reviewing-data-science-projects-7bfbc2919724 Peer Reviewing Data Science ProjectsMaking your work more error-proof using peer scrutinyShay PalachySMar 20 “Peer review is an important part of any creative activity…. The goal of this post,Continue readingWhat I Read: Peer Reviewing Data Science Projects

What I Read: Monitoring Machine Learning Models in Production

By Andrew Fairless on December 20, 2020December 23, 2020

https://christophergs.com/machine%20learning/2020/03/14/how-to-monitor-machine-learning-models/ Monitoring Machine Learning Models in ProductionA Comprehensive Guide14 March 2020 “Once you have deployed your machine learning model to production it rapidly becomes apparent that the work is notContinue readingWhat I Read: Monitoring Machine Learning Models in Production

What I Read: Guide to Graph Neural Networks

By Andrew Fairless on December 20, 2020December 8, 2020

https://medium.com/dair-ai/an-illustrated-guide-to-graph-neural-networks-d5564a551783 An Illustrated Guide to Graph Neural NetworksA breakdown of the inner workings of GNNs…Rishabh AnandMar 30 “Here, I’ll cover the basics of a simple Graph Neural Network (GNN) andContinue readingWhat I Read: Guide to Graph Neural Networks

What I Read: Diffusion Map for manifold learning

By Andrew Fairless on December 19, 2020December 8, 2020

https://randomwalk.in/python/ml/2020/03/14/Diffusion-Map.html Diffusion Map for manifold learning, Theory and Implementation “Manifold learning is an approach to non-linear dimensionality reduction…. In this blog, we learn one of the many techniques in manifoldContinue readingWhat I Read: Diffusion Map for manifold learning

What I Read: sub-linear deep learning algorithm

By Andrew Fairless on December 19, 2020December 4, 2020

https://www.kdnuggets.com/2020/03/deep-learning-breakthrough-sub-linear-algorithm-no-gpu.html Deep Learning Breakthrough: a sub-linear deep learning algorithm that does not need a GPU?By Anshumali Shrivastava, Rice University. “Backpropagation is not an efficient algorithm…. The core idea behind theContinue readingWhat I Read: sub-linear deep learning algorithm

Author: Andrew Fairless