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minireference.com | ||
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brenocon.com
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| | | | | [AI summary] The provided text is a collection of comments and discussions from a blog post that originally criticized artificial neural networks (ANNs) in 2008. The comments reflect a range of opinions and debates about the relationship between machine learning (ML) and statistics, with some users defending ML techniques like support vector machines (SVMs), probabilistic graphical models, and deep learning, while others argue for the importance of statistical methods. There are also discussions about the need for better communication between disciplines, the limitations of ML approaches, and the importance of understanding the underlying assumptions of models. The text includes recommendations for textbooks and courses, such as 'All of Statistics' and Andre... | |
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www.quantstart.com
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| | | | | Bayesian Statistics: A Beginner's Guide | |
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nobsstats.com
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peterbloem.nl
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| | | [AI summary] The text provides an in-depth explanation of the Fundamental Theorem of Algebra, which states that every non-constant polynomial of degree $ n $ has exactly $ n $ roots in the complex number system, counting multiplicities. It walks through the proof by first establishing that every polynomial has at least one complex root (using the properties of continuous functions and the complex plane), then using polynomial division to factor the polynomial into linear factors, and finally addressing the nature of roots (real vs. complex) and their multiplicities. The text also touches on the conjugate root theorem, which explains why complex roots of polynomials with real coefficients come in conjugate pairs. | ||
