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A Top Machine Learning Algorithm Explained: Support Vector Machines (SVM)

KDnuggets

Support Vector Machines (SVMs) are powerful for solving regression and classification problems. You should have this approach in your machine learning arsenal, and this article provides all the mathematics you need to know -- it's not as hard you might think.

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Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

A visual representation of generative AI – Source: Analytics Vidhya Generative AI is a growing area in machine learning, involving algorithms that create new content on their own. These algorithms use existing data like text, images, and audio to generate content that looks like it comes from the real world.

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From Rulesets to Transformers: A Journey Through the Evolution of SOTA in NLP

Mlearning.ai

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

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NLP-Powered Data Extraction for SLRs and Meta-Analyses

Towards AI

As the capabilities of high-powered computers and ML algorithms have grown, so have opportunities to improve the SLR process. New research has also begun looking at deep learning algorithms for automatic systematic reviews, According to van Dinter et al.

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A Non-Deep Learning Approach to Computer Vision

Heartbeat

Scale-Invariant Feature Transform (SIFT) This is an algorithm created by David Lowe in 1999. It’s a general algorithm that is known as a feature descriptor. After picking the set of images you desire to use, the algorithm will detect the keypoints of the images and store them in a database. It detects corners.

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Data-driven Attribution Modeling

Data Science Blog

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). Common algorithms include logistic regressions to easily predict the probability of conversion based on various features. References Zhao, K., Mahboobi, S.

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AI Emotion Recognition Using Computer Vision

Heartbeat

Genetic algorithms [ 1 ] are one way to detect faces in a digital image, followed by the Eigenface technique to verify the fitness of the region of interest. 2020 ) can be integrated to add greater weight to the core features. It is then re-trained to derive patterns of facial expressions using negative and positive values.

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