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statistical learning

Numerical stability showcase: Ranking with SoftMax or Boltzmann factor

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Preamble Image: Babylonian table for computation (Wikipedia)Probably, one of the most important aspects of computational work in quantitative fields, such as physics and data sciences is stability of numerical computations. It implies given inputs, outputs should not wildly deviates to large...

machine learning statistical learning statistical physics numerical analysis connectionist machine learning statistics

Full cross-validation and generating learning curves for time-series models

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Kindly reposted to KDnuggets by Gregory Piatetsky-ShapiroPreambleTime-series analysis is needed almost in any quantitative field and real-life systems that collects data over time, i.e., temporal datasets. Building predictive models on temporal datasets for future evolution of systems in...

machine learning deep learning learning-curve statistical learning learning theory cross-validation time-series statistics temporal

Book review: A tutorial introduction to the mathematics of deep learning

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Preamble Artificial Intelligence Engines:An introduction to the Mathematics of Deep Learning by Dr James V. Stone the book and Github repository. (c) 2019 Sebtel Press Deep learning and associated connectionist approaches are now applied routinely in industry and academic research from image...

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A simple and interpretable performance measure for a binary classifier

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Kindly reposted to KDnuggets by Gregory Piatetsky-Shapiro  Preamble The core application of machine learning models is a binary classification task. This appears in polyhedra of areas from medicine for diagnostic tests to credit risk decision making for consumers.  Techniques in building...

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Core principles of sustainable data science, machine learning and AI product development: Research as a core driver

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Kindly reposto to KDnuggets  by Gregory Piatetsky-Shapiro Preamble  Almost all businesses and industry embraced Machine learning (ML) technologies. Apart from ROI concerns, as it is an expensive endeavour to develop and deploy a service driven by ML techniques, sustainability as in going beyond...

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Teaching to machines: What is learning in machine learning entails?

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Preamble Ebbinghaus (WikipediaMachine Learning (ML) is now a de-facto skill for every quantitative job and almost every industry embraced it, even though fundamentals of the field is not new at all. However, what does it mean to teach to a machine? Unfortunately, for even moderate technical people...

machine learning data science data analysis statistical learning hebbian learning supervised learning gnu r learning theory function inference clustering classsification r hebbian theory r project

Understanding overfitting: an inaccurate meme in supervised learning

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Kindly reposted to KDnuggets by Gregory Piatetsky-Shapiro with the title Understanding overfitting: an inaccurate meme in machine learning Preamble There is a lot of confusion among practitioners regarding the concept of overfitting. It seems like, a kind of an urban legend or a meme, a folklore...

machine learning data science prediction statistical learning supervised learning gnu r cross-validation overtraining r programming overfitting regression statistics r r project regularisation