InTowards Data SciencebyVadim ArzamasovML Metamorphosis: Chaining ML Models for Optimized ResultsThe universal principle of knowledge distillation, model compression, and rule extractionOct 231
Ajay VermaModel Compression and Optimization: Techniques to Enhance Performance and Reduce SizeIn the realm of deep learning, model complexity has increased significantly, leading to the development of state-of-the-art (SOTA) models…Oct 18
Robert McMenemyAdvancing Hex Quantisation: Integrating Pruning, SVD, DCT, and Graph-Based Compression for Deep…IntroductionOct 3Oct 3
Anh TuanIntroduction to QuantizationIn this post, I’ll introduce an overview of neural network quantization, one method for reducing the size of deep learning models.May 21May 21
Bilal4 Compression Techniques for Language Models to Optimize Performance and EfficiencyIn the world of AI, the pursuit of larger and more powerful language models has been a constant trend. However, as MistralAI and others…Sep 27Sep 27
InTowards Data SciencebyVadim ArzamasovML Metamorphosis: Chaining ML Models for Optimized ResultsThe universal principle of knowledge distillation, model compression, and rule extractionOct 231
Ajay VermaModel Compression and Optimization: Techniques to Enhance Performance and Reduce SizeIn the realm of deep learning, model complexity has increased significantly, leading to the development of state-of-the-art (SOTA) models…Oct 18
Robert McMenemyAdvancing Hex Quantisation: Integrating Pruning, SVD, DCT, and Graph-Based Compression for Deep…IntroductionOct 3
Anh TuanIntroduction to QuantizationIn this post, I’ll introduce an overview of neural network quantization, one method for reducing the size of deep learning models.May 21
Bilal4 Compression Techniques for Language Models to Optimize Performance and EfficiencyIn the world of AI, the pursuit of larger and more powerful language models has been a constant trend. However, as MistralAI and others…Sep 27
Anish HilaryUnderstanding Eigenvalues and Eigenvectors: Enabling Deep Neural Network CompressionEigenvalues and Eigenvectors are fundamental concepts in linear algebra, widely utilized across diverse domains. In the context of deep…Apr 18
Nguyen Minh QuangKnowledge Distillation Explained: Model CompressionKnowledge distillation in machine learning refers transferring knowledge from larger “teacher” model to smaller “student” model.May 11
