AWS Machine Learning Blog

JUNE 3, 2024

To find the relationship between a numeric variable (like age or income) and a categorical variable (like gender or education level), we first assign numeric values to the categories in a way that allows them to best predict the numeric variable. Linear categorical to categorical correlation is not supported.

Generative AI 117

Generative AI Categorization Auto-complete Auto-classification 117

Topbots

JUNE 22, 2023

So, to make a viable comparison, I had to: Categorize the dataset scores into Positive , Neutral , or Negative labels. This evaluation assesses how the accuracy (y-axis) changes regarding the threshold (x-axis) for categorizing the numeric Gold-Standard dataset for both models. First, I must be honest. Then, I made a confusion matrix.

Machine Learning 107

Machine Learning ChatGPT Natural Language Processing Categorization 107

Viso.ai

DECEMBER 6, 2023

Image Classification Image classification tasks involve CV models categorizing images into user-defined classes for various applications. Based on the presence of a tiger, the entire image is categorized as such. The model secured first and second positions in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) 2014.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Categorization 52

Viso.ai

JANUARY 2, 2024

VGGNet , introduced by Simonyan and Zisserman in 2014, emphasized the importance of depth in CNN architectures through its 16-19 layer CNN network. Text Processing with CNNs In text processing, CNNs are remarkably efficient, particularly in tasks like sentiment analysis, topic categorization, and language translation.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Data Scarcity 52

Heartbeat

AUGUST 21, 2023

AlexNet was created to categorize photos in the ImageNet dataset, which contains approximately 1 million images divided into 1,000 categories. GoogLeNet: is a highly optimized CNN architecture developed by researchers at Google in 2014. It has eight layers, five of which are convolutional and three fully linked.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Natural Language Processing Deep Learning 52

ML Review

MARCH 31, 2019

In 2014, a group of researchers at Google and NYU found that it was far too easy to fool ConvNets with an imperceivable, but carefully constructed nudge in the input. But by 2014, ConvNets had become powerful enough to start surpassing human accuracy on a number of visual recognition tasks. What are adversarial attacks? confidence.

Neural Network 52

Neural Network Machine Learning Deep Learning Explainability 52

Mlearning.ai

MARCH 31, 2023

Getting the Metrics and Loss Functions Since our model must implement two tasks — classification and regression — we need two different Loss Functions : One for the classification task: we may use any Loss Function usually found in only-classification tasks like Categorical Crossentropy. and model (only 3,235,014 parameters!)

Deep Learning 98

Deep Learning Machine Learning Python Categorization 98