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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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Exploring the dynamic fusion of AI and the IoT

Dataconomy

By harnessing the power of AI in IoT, we can create intelligent ecosystems where devices seamlessly communicate, collaborate, and make intelligent choices to improve our lives. Let’s explore the fascinating intersection of these two technologies and understand how AI enhances the functionalities of IoT.

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NLP-Powered Data Extraction for SLRs and Meta-Analyses

Towards AI

Last Updated on July 20, 2023 by Editorial Team Author(s): Gaugarin Oliver Originally published on Towards AI. It’s also an area that stands to benefit most from automated or semi-automated machine learning (ML) and natural language processing (NLP) techniques. This study by Bui et al.

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AI Drug Discovery: How It’s Changing the Game

Becoming Human

AI drug discovery is exploding. Overhyped or not, investments in AI drug discovery jumped from $450 million in 2014 to a whopping $58 billion in 2021. AI has already helped identify promising candidate therapeutics, and it didn’t take years but months or even days. We will look at success stories, AI benefits, and limitations.

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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. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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How Machines Learn: The Power of Gradient Descent

Towards AI

Last Updated on May 3, 2023 by Editorial Team Author(s): Ulrik Thyge Pedersen Originally published on Towards AI. Gradient descent is widely used in various machine learning models, such as linear regression, logistic regression, and neural networks.

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Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction

Towards AI

Last Updated on February 20, 2024 by Editorial Team Author(s): Vaishnavi Seetharama Originally published on Towards AI. Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms.