Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

NLP 98

NLP Neural Network Natural Language Processing Convolutional Neural Networks 98

Viso.ai

FEBRUARY 25, 2023

Vision Transformer (ViT) have recently emerged as a competitive alternative to Convolutional Neural Networks (CNNs) that are currently state-of-the-art in different image recognition computer vision tasks. Transformer models have become the de-facto status quo in Natural Language Processing (NLP).

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Lexalytics

APRIL 5, 2021

A paper that exemplifies the Classifier Cage Match era is LeCun et al [ 109 ], which pits support vector machines (SVMs), k-nearest neighbor (KNN) classifiers, and convolution neural networks (CNNs) against each other to recognize images from the NORB database. 90,575 trainable parameters, placing it in the small-feature regime.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Snorkel AI

MARCH 1, 2023

This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Radford et al.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

Sebastian Ruder

JANUARY 19, 2021

The selection of areas and methods is heavily influenced by my own interests; the selected topics are biased towards representation and transfer learning and towards natural language processing (NLP).  2020 saw the development of ever larger language and dialogue models such as Meena ( Adiwardana et al.,

NLP 52

NLP ML Computer Vision Neural Network 52

Marek Rei

NOVEMBER 12, 2019

Below you will find short summaries of a number of different research papers published in the areas of Machine Learning and Natural Language Processing in the past couple of years (2017-2019). Improving Language Understanding by Generative Pre-Training Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever.

Machine Learning 52

Machine Learning NLP Neural Network BERT 52

AWS Machine Learning Blog

FEBRUARY 10, 2023

Quantitative evaluation We utilize 2018–2020 season data for model training and validation, and 2021 season data for model evaluation. He is broadly interested in Deep Learning and Natural Language Processing. and Big Data Bowl Kaggle Zoo solution ( Gordeev et al. ). Each season consists of around 17,000 plays.

Computer Vision 73

Computer Vision Machine Learning ML Convolutional Neural Networks 73