Demystifying

In my work experiences (in the field of Big Data analysis and Data Engineering), the projects are always different, but they always follow…Continue reading on Towards Data Science » In my work experiences (in the field of Big Data analysis and Data Engineering), the projects are always different, but they always follow…Continue reading on Towards Data Science » FOLLOW US ON GOOGLE NEWS Read original article here Denial of responsibility! Techno Blender is an automatic aggregator of the all…

Mistral AI’s open-source Mixtral 8x7B model made a lot of waves — here’s what’s under the hoodContinue reading on Towards Data Science » Mistral AI’s open-source Mixtral 8x7B model made a lot of waves — here’s what’s under the hoodContinue reading on Towards Data Science » FOLLOW US ON GOOGLE NEWS Read original article here Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In each…

A data scientist’s guide to AI-powered content creationContinue reading on Towards Data Science » A data scientist’s guide to AI-powered content creationContinue reading on Towards Data Science » FOLLOW US ON GOOGLE NEWS Read original article here Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners, all materials to their authors. If you are…

Navigating through uncertainty in data for extracting global statistical insightsIntroductionConfidence intervals are of the most important concepts in statistics. In data science, we often need to calculate statistics for a given data variable. The common problem we encounter is the lack of full data distribution. As a result, statistics are calculated only for a subset of data. The obvious drawback is that the computed statistics of the data subset might differ a lot from the real value, based on all possible values.An…

Uncovering the power and applications of a rising deep learning AlgorithmContinue reading on Towards Data Science » Uncovering the power and applications of a rising deep learning AlgorithmContinue reading on Towards Data Science » FOLLOW US ON GOOGLE NEWS Read original article here Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners, all materials to…

Demystifying GQA — Grouped Query Attention for Efficient LLM Pre-trainingThe variant of multi-head attention powering LLMs like LLaMA-2, Mistral7B, etc.A “Group” of Llamas (Source — Image created by the author using Dalle-3)In the previous article on training large-scale models, we looked at LoRA. In this article, we will examine another strategy adopted by different large language models for efficient training — Grouped Query Attention (GQA). In short, Grouped Query Attention (GQA) is a generalization of multi-head…

Books on music are often written either about its practical or theoretical aspects. Music & Mind: Demystifying Thumri Maestros focuses on the psychological aspect of classical Hindustani music, especially the thumri genre. Author Meenakshi Prasad, herself a thumri singer trained under Vidushi Savita Devi, is a postgraduate in psychology. This book, that explores the influence of psychology in the emergence and success of an artist, combines the author’s excellence in her subject and in the realm of music. A…

Explore L1 & L2 Regularization as Bayesian PriorsContinue reading on Towards Data Science » Explore L1 & L2 Regularization as Bayesian PriorsContinue reading on Towards Data Science » FOLLOW US ON GOOGLE NEWS Read original article here Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners, all materials to their authors. If you are the owner of the…

Why L0.5, L3, and L4 Regularizations Are UncommonPhoto by Kelvin Han on UnsplashWelcome back to the third installment of ‘Courage to Learn ML: Demystifying L1 & L2 Regularization’ Previously, we delved into the purpose of regularization and decoded L1 and L2 methods through the lens of Lagrange Multipliers.Continuing our journey, our mentor-learner duo will further explore L1 and L2 regularization using Lagrange Multipliers.In this article, we’ll tackle some intriguing questions that might have crossed your mind. If…

Comprehend the underlying purpose of L1 and L2 regularizationPhoto by Holly Mandarich on UnsplashWelcome to the ‘Courage to learn ML’, where we kick off with an exploration of L1 and L2 regularization. This series aims to simplify complex machine learning concepts, presenting them as a relaxed and informative dialogue, much like the engaging style of “The Courage to Be Disliked,” but with a focus on ML.These Q&A sessions are a reflection of my own learning path, which I’m excited to share with you. Think of this as a…