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Top 10 Explainable AI (XAI) Frameworks

Marktechpost

The increasing complexity of AI systems, particularly with the rise of opaque models like Deep Neural Networks (DNNs), has highlighted the need for transparency in decision-making processes. The Institute for Ethical AI & ML maintains the XAI library. Image Source 10.

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Artificial Neural Network: A Comprehensive Guide

Pickl AI

Summary: Artificial Neural Network (ANNs) are computational models inspired by the human brain, enabling machines to learn from data. Introduction Artificial Neural Network (ANNs) have emerged as a cornerstone of Artificial Intelligence and Machine Learning , revolutionising how computers process information and learn from data.

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This Machine Learning Research from Tel Aviv University Reveals a Significant Link between Mamba and Self-Attention Layers

Marktechpost

Recent studies have highlighted the efficacy of Selective State Space Layers, also known as Mamba models, across various domains, such as language and image processing, medical imaging, and data analysis. These matrices are leveraged to develop class-agnostic and class-specific tools for explainable AI of Mamba models.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

Machine learning can then “learn” from the data to create insights that improve performance or inform predictions. Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis.

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Financial Data & AI: The Future of Business Intelligence

Defined.ai blog

Businesses must understand how to implement AI in their analysis to reap the full benefits of this technology. In the following sections, we will explore how AI shapes the world of financial data analysis and address potential challenges and solutions.

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20 Best Artificial Intelligence Books For Beginners in 2025

Pickl AI

We aim to guide readers in choosing the best resources to kickstart their AI learning journey effectively. From neural networks to real-world AI applications, explore a range of subjects. Using simple language, it explains how to perform data analysis and pattern recognition with Python and R.

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AI in Finance – Top Computer Vision Tools and Use Cases

Viso.ai

With advancements in machine learning (ML) and deep learning (DL), AI has begun to significantly influence financial operations. Arguably, one of the most pivotal breakthroughs is the application of Convolutional Neural Networks (CNNs) to financial processes. 2: Automated Document Analysis and Processing No.3: