Tag: #AI
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A Deep Dive into Transformers and its Function
Introduction: In recent years, Generative AI has witnessed a paradigm shift with the introduction of transformer models. These models, characterized by their attention mechanisms, have revolutionized natural language processing (NLP) and other generative tasks. In this blog post, we’ll explore the transformer architecture, its applications in NLP, and its extension to other creative domains. Understanding…
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Optimizing Deep Learning: A Comprehensive Guide to Batch Normalization
Batch Normalization (BN) is a technique used in deep learning to improve the training of deep neural networks by reducing the internal covariate shift problem. This problem occurs when the distribution of the inputs to each layer of the network changes during training, making it difficult to train the network effectively. BN addresses this issue…
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Effective Feature Selection Techniques for Improved Model Performance
Introduction Feature selection is a crucial step in building machine learning models, as irrelevant or redundant features can hinder model performance. In this blog post, we will explore two essential feature selection methods and apply them to a real-world dataset: eliminating low variance features and recursive feature elimination using cross-validation. Eliminating Low Variance Features: One…