Data Science Dojo

MAY 27, 2024

A visual representation of discriminative AI – Source: Analytics Vidhya Discriminative modeling, often linked with supervised learning, works on categorizing existing data. This breakthrough has profound implications for drug development, as understanding protein structures can aid in designing more effective therapeutics.

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Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].”

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PyImageSearch

JANUARY 2, 2023

Figure 1: Global Funding in Health Tech Companies (source: Mrazek and O’Neill, 2020 ). This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. This series is about CV and DL for Industrial and Big Business Applications.

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Mlearning.ai

APRIL 8, 2023

The earlier models that were SOTA for NLP mainly fell under the traditional machine learning algorithms. These included the Support vector machine (SVM) based models. 2003) “ Support-vector networks ” by Cortes and Vapnik (1995) Significant people : David Blei Corinna Cortes Vladimir Vapnik 4.

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Towards AI

JULY 20, 2023

Other NLP techniques commonly used to automate parts of the SLR process are text vector (used in research identification and primary study selection), singular value decomposition (primary study selection), and latent semantic analysis models (primary study selection).

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Data Science Blog

OCTOBER 20, 2024

Finally, Shapley value and Markov chain attribution can also be combined using an ensemble attribution model to further reduce the generalization error (Gaur & Bharti 2020). Moreover, random forest models as well as support vector machines (SVMs) are also frequently applied. References Zhao, K., Mahboobi, S.

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Heartbeat

MAY 22, 2023

2020 ) can be integrated to add greater weight to the core features. Schematic diagram of the overall framework of Emotion Recognition System [ Source ] The models that are used for AI emotion recognition can be based on linear models like Support Vector Machines (SVMs) or non-linear models like Convolutional Neural Networks (CNNs).

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