generalization – Page 4 – Andrew Fairless, Ph.D.

What I Read: Tabular Data, Deep Learning is Not All You Need

By Andrew Fairless on July 14, 2021June 22, 2021

https://arxiv.org/abs/2106.03253v1 Tabular Data: Deep Learning is Not All You NeedRavid Shwartz-Ziv, Amitai Armon “Our study shows that XGBoost outperforms these deep models across the datasets, including datasets used in theContinue readingWhat I Read: Tabular Data, Deep Learning is Not All You Need

What I Read: Comprehensive Guide to Ensemble Learning

By Andrew Fairless on June 29, 2021June 7, 2021

https://www.kdnuggets.com/2021/05/comprehensive-guide-ensemble-learning.html A Comprehensive Guide to Ensemble Learning – Exactly What You Need to KnowThis article covers ensemble learning methods, and exactly what you need to know in order to understandContinue readingWhat I Read: Comprehensive Guide to Ensemble Learning

What I Read: Dataset Curation for NLP Projects

By Andrew Fairless on June 15, 2021May 30, 2021

https://www.kdnuggets.com/2021/05/4-tips-dataset-curation-nlp-projects.html 4 Tips for Dataset Curation for NLP ProjectsBy Paul Barba, Chief Scientist, Lexalytics. “After many years of painfully learned lessons from managing and implementing AI and ML projects, I’veContinue readingWhat I Read: Dataset Curation for NLP Projects

What I Read: Be Careful Interpreting Predictive Models, Causal Insights

By Andrew Fairless on June 9, 2021May 30, 2021

https://towardsdatascience.com/be-careful-when-interpreting-predictive-models-in-search-of-causal-insights-e68626e664b6 Be Careful When Interpreting Predictive Models in Search of Causal InsightsA careful exploration of the pitfalls of trying to extract causal insights from modern predictive machine learning models.Scott LundbergContinue readingWhat I Read: Be Careful Interpreting Predictive Models, Causal Insights

What I Read: Rip van Winkle’s Razor, Adaptive Data Analysis

By Andrew Fairless on April 17, 2021April 10, 2021

http://www.offconvex.org/2021/04/07/ripvanwinkle/ Rip van Winkle’s Razor, a Simple New Estimate for Adaptive Data AnalysisSanjeev Arora, Yi ZhangApr 7, 2021 “Can you trust a model whose designer had access to the test/holdoutContinue readingWhat I Read: Rip van Winkle’s Razor, Adaptive Data Analysis

What I Read: Deep learning model compression

By Andrew Fairless on April 10, 2021April 10, 2021

https://rachitsingh.com/deep-learning-model-compression/ Deep learning model compressionRachit SinghWritten March 26, 2021 “Researchers and practitioners have come up with many methods for optimizing neural networks to run faster or with less memory usage.Continue readingWhat I Read: Deep learning model compression

What I Read: Generalization in Deep Learning

By Andrew Fairless on March 31, 2021April 3, 2021

https://ai.googleblog.com/2021/03/a-new-lens-on-understanding.html A New Lens on Understanding Generalization in Deep LearningWednesday, March 10, 2021Hanie Sedghi, Google Research and Preetum Nakkiran, Harvard University “…we find that models that train quickly on infiniteContinue readingWhat I Read: Generalization in Deep Learning

What I Read: Deep learning, black box

By Andrew Fairless on March 21, 2021March 7, 2021

https://bdtechtalks.com/2021/01/11/concept-whitening-interpretable-neural-networks/ Deep learning doesn’t need to be a black boxBen DicksonJanuary 11, 2021 “The innerworkings of neural networks are often a mystery…. scientists at Duke University propose “concept whitening,” aContinue readingWhat I Read: Deep learning, black box

What I Read: ML Models are Missing Contracts

By Andrew Fairless on March 15, 2021March 7, 2021

https://gradio.app/blog/missing-contracts Machine Learning Models are Missing ContractsWhy pretrained machine learning models are often unusable and irreproducible — and what we can do about it.By Abubakar Abid “We need to provideContinue readingWhat I Read: ML Models are Missing Contracts

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