natural language processing – Page 17

What I Read: Zero-Shot Learning

By Andrew Fairless on May 6, 2021April 13, 2021

https://www.kdnuggets.com/2021/04/zero-shot-learning.html Zero-Shot Learning: Can you classify an object without seeing it before?Developing machine learning models that can perform predictive functions on data it has never seen before has become anContinue readingWhat I Read: Zero-Shot Learning

What I Read: Reducing High Cost of Training NLP Models

By Andrew Fairless on March 29, 2021April 3, 2021

https://www.asapp.com/blog/reducing-the-high-cost-of-training-nlp-models-with-sru/ Reducing the High Cost of Training NLP Models With SRU++By Tao Lei, PhDResearch Leader and Scientist at ASAPP “The Transformer architecture was proposed to accelerate model training in NLP….Continue readingWhat I Read: Reducing High Cost of Training NLP Models

What I Read: Language Model Fine-tuning

By Andrew Fairless on March 26, 2021March 7, 2021

https://ruder.io/recent-advances-lm-fine-tuning/ Recent Advances in Language Model Fine-tuningThis article provides an overview of recent methods to fine-tune large pre-trained language models.Sebastian Ruder24 Feb 2021 “While pre-training is compute-intensive, fine-tuning can beContinue readingWhat I Read: Language Model Fine-tuning

What I Read: Transformer Networks to Answer Questions About Images

By Andrew Fairless on March 13, 2021March 7, 2021

https://medium.com/dataseries/microsoft-uses-transformer-networks-to-answer-questions-about-images-with-minimum-training-f978c018bb72 Microsoft Uses Transformer Networks to Answer Questions About Images With Minimum TrainingUnified VLP can understand concepts about scenic images by using pretrained models.Jesus RodriguezJan 12 “Can we build deepContinue readingWhat I Read: Transformer Networks to Answer Questions About Images

What I Read: Neural Text Generation

By Andrew Fairless on March 11, 2021March 7, 2021

https://lilianweng.github.io/lil-log/2021/01/02/controllable-neural-text-generation.html Controllable Neural Text GenerationJan 2, 2021Lilian Weng “How to steer a powerful unconditioned language model? In this post, we will delve into several approaches for controlled content generation withContinue readingWhat I Read: Neural Text Generation

What I Read: Why I’m lukewarm on graph neural networks

By Andrew Fairless on March 10, 2021March 7, 2021

https://www.singlelunch.com/2020/12/28/why-im-lukewarm-on-graph-neural-networks/ Why I’m lukewarm on graph neural networksMatt RangerFebruary 16, 2020 “I’m only lukewarm on Graph Neural Networks (GNNs)…. I think some progress can come of this research, but we’reContinue readingWhat I Read: Why I’m lukewarm on graph neural networks

What I Read: How Transformers work

By Andrew Fairless on March 9, 2021March 7, 2021

https://theaisummer.com/transformer/ How Transformers work in deep learning and NLP: an intuitive introductionNatural Language ProcessingNikolas AdaloglouDec 24, 2020 “In my opinion, transformers are not so hard to grasp. It’s the combinationContinue readingWhat I Read: How Transformers work

What I Read: Interpretability in Machine Learning

By Andrew Fairless on February 20, 2021January 21, 2021

https://thegradient.pub/interpretability-in-ml-a-broad-overview/ Interpretability in Machine Learning: An Overview21.Nov.2020Owen Shen “Broadly, interpretability focuses on the how. It’s focused on getting some notion of an explanation for the decisions made by our models….Continue readingWhat I Read: Interpretability in Machine Learning

What I Read: HuggingFace Transformers

By Andrew Fairless on February 18, 2021January 18, 2021

https://medium.com/georgian-impact-blog/how-to-incorporate-tabular-data-with-huggingface-transformers-b70ac45fcfb4 How to Incorporate Tabular Data with HuggingFace TransformersGeorgianOct 23 “At Georgian, we find ourselves working with supporting tabular feature information as well as unstructured text data. We found thatContinue readingWhat I Read: HuggingFace Transformers

What I Read: Revisiting Sutton’s Bitter Lesson for AI

By Andrew Fairless on February 15, 2021January 18, 2021

https://blog.exxactcorp.com/compute-goes-brrr-revisiting-suttons-bitter-lesson-artificial-intelligence/ Deep LearningCompute Goes Brrr: Revisiting Sutton’s Bitter Lesson for Artificial IntelligenceMarketing, October 27, 2020 “The main driver of AI progress, according to Sutton, is the increasing availability of computeContinue readingWhat I Read: Revisiting Sutton’s Bitter Lesson for AI

Tag: natural language processing