Logistic regression is a supervised machine learning algorithm used in classification tasks where a target variable $y$ may take $K$ possible values, and we are interested in labeling an observation $\mathbf{x}$ composed of $N$ features/predictors. In particular, logistic regression is used in binary classification tasks, i.e., cases where $K=2$. However,...
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I am a PhD in Computer Science with a background in Electronics Engineering.
I am currently looking for a job! ... voilà my CV, both the academic (with a list of publications) and 1-page versions.
Linear and Polynomial Regression
Linear and polynomial regression are supervised machine learning algorithms used, as their names indicate, to perform regression tasks, i.e., to estimate the values of a continuous response/target variable $y$.
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Machine Learning and Pattern Recognition
As human beings, we like understanding what surrounds us, either for the simple sake of knowing or because this gives us predictability. In that sense, in many situations it arrives that we have a problem that we want to model, e.g., from a phenomenon that depends only on basic physics...
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Classification relying on Bayes or Bayes classifiers
The objective is to determine to which class $\hat{y}$ an unlabelled observation $x$ belongs to, out of $K$ available. We assume that $x$ is composed of $n$ features/predictors, i.e., $x=(x_1,\ldots,x_n)$.
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Finally a PhD, no longer a candidate!
I am glad to tell you that I finished my PhD with a defense that went great a couple of days ago, I am very happy :)
I was lucky and my presentation got recorded, thus I want to share it with you! I hope you enjoy it!
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