Viso.ai

FEBRUARY 11, 2024

It is a technique used in computer vision to identify and categorize the main content (objects) in a photo or video. 2011 – A good ILSVRC image classification error rate is 25%. 2012 – A deep convolutional neural net called AlexNet achieves a 16% error rate. parameters, achieving an accuracy of around 84%.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 52

John Snow Labs

DECEMBER 26, 2023

On the other hand, Sentiment analysis is a method for automatically identifying, extracting, and categorizing subjective information from textual data. Sentiment Analysis Using Simplified Long Short-term Memory Recurrent Neural Networks. The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011).

Neural Network 52

Neural Network Computational Linguistics NLP Natural Language Processing 52

AWS Machine Learning Blog

APRIL 6, 2023

The point cloud-based neural network model is further trained using this data to learn the parameters of the product lifecycle curve (see the following figure). These features include product fabrication techniques and other related categorical information related to the products. First, we introduced a point cloud-based method.

Machine Learning 86

Machine Learning ML Categorization Data Scientist 86

Explosion

MARCH 17, 2019

In 2011, deep learning methods were proving successful for NLP, and techniques for pretraining word representations were already in use. A range of techniques for pretraining further layers of the network were proposed over the years, as the deep learning hype took hold. when we switched over to neural network models.

NLP 52

NLP Python Neural Network Natural Language Processing 52

Explosion

FEBRUARY 12, 2017

A neural bag-of-words model for text-pair classification When designing a neural network for a text-pair task, probably the most important decision is whether you want to represent the meanings of the texts independently , or jointly. Most NLP neural networks start with an embedding layer.

Neural Network 40

Neural Network Deep Learning Natural Language Processing NLP 40

Viso.ai

JANUARY 16, 2024

The AI community categorizes N-shot approaches into few, one, and zero-shot learning. Matching Networks: The algorithm computes embeddings using a support set, and one-shot learns by classifying the query data sample based on which support set embedding is closest to the query embedding – source.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Algorithm 52