I’m moving my blog out of Medium.com. My priorities have not changed - the goal of my blog posts will be to explain why/how things work from first principles. Majority of the articles will be based on machine learning and deep learning. The posts are meant to intrigue and challenge theoretically sound individuals - therefore, unlike the posts that discuss ‘industry solutions’ without sharing why/how things work, the (series of) posts will dive head-first into the details and not hide behind keywords or discuss results/empirical performance as “end justifies the means”. Relevant basics and research papers will be mentioned/referenced where required.
Most posts on machine/deep learning are mathematical. Some posts go into practical experimentation using artificial/toy data sets.
The blog structure was forked from Renan Franca’s website. Some references to Renan Franca’s pages were intentionally left - I plan to replace some of those with links to another blog where I wish to write about “industry solutions”.
Posts
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‘Manufacturing’ polynomials using a sigmoid neural network - practicum
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‘Manufacturing’ polynomials using a sigmoid neural network
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Understanding the Expressive Power of ReLU Networks
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Ridge Regularization on Linear Regression and Deep Learning Models
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Lasso Regularization on Linear Regression and Deep Learning Models
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Lasso, Ridge and Dropout Regularization in Deep Learning — their effects on Collinearity
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CNN vs Fully-Connected Network for Image Processing
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Equivalence of MLE and OLS in Linear Regression
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Simple Linear Regression and ANOVA
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Introduction to Bayesian Statistics - Part 2
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Bayes Theorem - The Basic Math
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Introduction to Bayesian Statistics - Part 1
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Applications of Bayes Theorem in Medicine
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A Short Note on Regularization
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OLS Linear Regression: Hyperplane of Zero Net Force and Torque
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