Pickl AI

JANUARY 26, 2025

Convolutional Neural Networks (CNNs) Convolutional Neural Networks ( CNNs ) are specialised Deep Learning models that process and analyse visual data. Transformers are the foundation of many state-of-the-art architectures, such as BERT and GPT.

Deep Learning 52

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 52

Mlearning.ai

APRIL 8, 2023

With the rise of deep learning (deep learning means multiple levels of neural networks) and neural networks, models such as Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs) began to be used in NLP. 2018) “ Language models are few-shot learners ” by Brown et al.

NLP 98

NLP Neural Network Natural Language Processing Convolutional Neural Networks 98

ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out his talk, “ Bagging to BERT — A Tour of Applied NLP ,” there! In the first example, we’ll be defining an architecture based on a Convolutional Neural Network (CNN) The dataset We’ll be using the same dataset as last time; a collection of 50k reviews from IMDB which are labeled as either positive or negative.

Deep Learning 98

Deep Learning Convolutional Neural Networks NLP Neural Network 98

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. The base model of BERT [ 103 ] had 12 (!) Hinton (again!)

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Mlearning.ai

JUNE 8, 2023

A few embeddings for different data type For text data, models such as Word2Vec , GLoVE , and BERT transform words, sentences, or paragraphs into vector embeddings. Images can be embedded using models such as convolutional neural networks (CNNs) , Examples of CNNs include VGG , and Inception. using its Spectrogram ).

Machine Learning 52

Machine Learning BERT Neural Network OpenAI 52

Marek Rei

NOVEMBER 12, 2019

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. Evaluations on CoNLL 2014 and JFLEG show a considerable improvement over previous best results of neural models, making this work comparable to state-of-the art on error correction.

Machine Learning 52

Machine Learning NLP Neural Network BERT 52

NLP People

JULY 24, 2019

Especially pre-trained word embeddings such as Word2Vec, FastText and BERT allow NLP developers to jump to the next level. Neural Networks are the workhorse of Deep Learning (cf. White (2014). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. References E. Cambria and B.

NLP 52

NLP Neural Network Deep Learning Natural Language Processing 52