Softmax is one of the most important functions for neural networks. It also has some interesting properties that we list here. This function is part of The Exponential Family, one can also see that the sigmoid function is a particular case of this softmax, just two variables. Sometimes this could be seen as a relaxation of the action potential inspired by neuroscience (See The Neuron for a little bit more about neurons)....
PAC Learning is one of the most famous theories in learning theory. Learning theory concerns in answering questions like: What is learnable? Somewhat akin to La macchina di Turing for computability theory. How well can you learn something? PAC is a framework that allows to formally answer these questions. Now there is also a bayesian version of PAC in which there is a lot of research. Some definitions Empirical Risk Minimizer and Errors The empirical risk minimizer is defined as $$ \arg \min_{\hat{c} \in \mathcal{H}} \hat{R}_{n}(\hat{c}) $$ Where the inside is the empirical error....
(Schulman et al. 2017) è uno degli articoli principali che praticamente hanno dato via al campo. Anche questo è buono per Policy gradients: https://lilianweng.github.io/posts/2018-04-08-policy-gradient/ Introduzione a PPO References [1] Schulman et al. “Proximal Policy Optimization Algorithms” 2017
Introduzione a Naïve Bayes NOTE: this note should be reviewed after the course I took in NLP. This is a very old note, not even well written. Bisognerebbe in primo momento avere benissimo in mente il significato di probabilità condizionata e la regola di naive Bayes in seguito. Bayes ad alto livello 🟩 Da un punto di vista intuitivo non è altro che predire la cosa che abbiamo visto più spesso in quello spazio Assunzioni principali per naïve Bayes 🟩 I sample di input sono condizionalmente indipendenti uno con l’altro....
Introduction to the course Machine learning offers a new way of thinking about reality: rather than attempting to directly capture a fragment of reality, as many traditional sciences have done, we elevate to the meta-level and strive to create an automated method for capturing it. This first lesson will be more philosophical in nature. We are witnessing a paradigm shift in the sense described by Thomas Kuhn in his theory of scientific revolutions....