AWS Machine Learning Blog

APRIL 6, 2023

These features include product fabrication techniques and other related categorical information related to the products. For example, in the 2019 WAPE value, we trained our model using sales data between 2011–2018 and predicted sales values for the next 12 months (2019 sale). We next calculated the MAPE for the actual sales values.

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Machine Learning ML Categorization Data Scientist 108

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. Image classification employs AI-based deep learning models to analyze images and perform object recognition, as well as a human operator. 2011 – A good ILSVRC image classification error rate is 25%.

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Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Viso.ai

JANUARY 16, 2024

Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks. The AI community categorizes N-shot approaches into few, one, and zero-shot learning. Get a demo here. Let’s discuss each in more detail.

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Neural Network Computer Vision Convolutional Neural Networks Algorithm 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. Learning Word Vectors for Sentiment Analysis. The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011). abs/2005.03993 Andrew L. Maas, Raymond E.

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Neural Network Computational Linguistics NLP Natural Language Processing 52

Mlearning.ai

JULY 30, 2023

With most ML use cases moving to deep learning, models’ opacity has increased significantly. Next, there are categorical features, usually represented as small one-hot vectors. fall under categorical features. Most feature-importance algorithms deal very well with dense and categorical features. 2825–2830, 2011.

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Python Machine Learning Categorization Explainability 52

Explosion

FEBRUARY 12, 2017

In this post, I’ll explain how to solve text-pair tasks with deep learning, using both new and established tips and technologies. The SNLI dataset is over 100x larger than previous similar resources, allowing current deep-learning models to be applied to the problem. This gives us two 2d arrays — one per sentence.

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Neural Network Deep Learning Natural Language Processing NLP 40

Heartbeat

OCTOBER 9, 2023

Artificial Intelligence (AI) Integration: AI techniques, including machine learning and deep learning, will be combined with computer vision to improve the protection and understanding of cultural assets. Preservation of cultural heritage and natural history through game-based learning. Ahmad, M., & Selviandro, N.

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Computer Vision Algorithm Deep Learning Machine Learning 52