Recursos sobre manejo de la incertidumbre y probabilidad por un agente inteligente, módulo de Modelos de Inteligencia Artificial

Solving hangman using probability

Deliverables relating to the Foundations of Data Science University Unit

Project for the course ENPM667 @ UMD. Code base and install instructions for a Point Cloud Regression and Camera Pose Estimation network using a Kalman Filter based loss function.

Elements of AI: Building AI - Advanced is an online course by Reaktor and University of Helsinki worth 2 ECTS.

Classification of image pixel into 2 classes using Baye's Decision Rule

All exercises for the course Elements of AI - Building AI

A simple 1-dimensional Gaussian Naïve Bayes Classifier.

The Matlab source code for basic probability used in information theory.

Using 2d histogram filter for localization

Kidnapped Vehicle (project 6 of 9 from Udacity Self-Driving Car Engineer Nanodegree)

Kalman filter finds the most optimum averaging factor for each consequent state. Also somehow remembers a little bit about the past states.

This course covers topics such as overview of sets, counting principles, probability, conditional probability and Bayes’ Rule, discrete Random Variables, continuous Random Variables, Bayesian inference, central limit theorem, regression and Markov Chains

This repository is made as supplementary material for a tutorial. The tutorial shows how to use Recurrent Neural Nets as generative models.

Uses some user input, data from the World Values Survey <www.worldvaluessurvey.org>, and Bayes Rule to guess a number of beliefs the user might have. STATUS: In progress.

A website to simulate book suggestion using Bayes rule