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Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

In the recent discussion and advancements surrounding artificial intelligence, there’s a notable dialogue between discriminative and generative AI approaches. These methodologies represent distinct paradigms in AI, each with unique capabilities and applications. What is Generative AI?

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Headroom for AI development

Machine Learning (Theory)

Support Vector Machines were disrupted by deep learning, and convolutional neural networks were displaced by transformers. As an example, the speech recognition community spent decades focusing on Hidden Markov Models at the expense of other architectures, before eventually being disrupted by advancements in deep learning.

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Data science techniques

Dataconomy

Among the most significant models are non-linear models, support vector machines, and linear regression. Support vector machines (SVM) Support Vector Machines are a robust classification technique in machine learning.

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What is Data-driven vs AI-driven Practices?

Pickl AI

Summary: The article explores the differences between data driven and AI driven practices. Data-driven and AI-driven approaches have become key in how businesses address challenges, seize opportunities, and shape their strategic directions.

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Clustering with Scikit-Learn: a Gentle Introduction

Towards AI

Author(s): Riccardo Andreoni Originally published on Towards AI. Learn how to apply state-of-the-art clustering algorithms efficiently and boost your machine-learning skills.Image source: unsplash.com. Join thousands of data leaders on the AI newsletter. Published via Towards AI From research to projects and ideas.

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Classifiers in Machine Learning

Pickl AI

Examples include: Spam vs. Not Spam Disease Positive vs. Negative Fraudulent Transaction vs. Legitimate Transaction Popular algorithms for binary classification include Logistic Regression, Support Vector Machines (SVM), and Decision Trees. These models can detect subtle patterns that might be missed by human radiologists.

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Rustic Learning: Machine Learning in Rust Part 2: Regression and Classification

Towards AI

Last Updated on April 6, 2023 by Editorial Team Author(s): Ulrik Thyge Pedersen Originally published on Towards AI. Photo by David Schultz on Unsplash Linfa Linfa is a Rust-based machine-learning library that offers a wide range of algorithms for regression, classification, clustering, and other tasks. Published via Towards AI