Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real-world datasets.

PHP implementation of statistical probability distributions: normal distribution, beta distribution, gamma distribution and more.

A MATLAB project which applies the central limit theorem on PDFs and CDFs of different probability distributions.

PyPi package for modelling Probability distributions

Fast generation of long sequencies of bernoulli-distributed random variables

Reinforcement Learning (COMP 579) Project

In probability theory and statistics, the Bernoulli distribution, named after Swiss mathematician Jacob Bernoulli, is the discrete probability distribution of a random variable which takes the value 1 with probability and the value 0 with probability, in this example we will be able to visualize that in graphics mode

My works for EE 511 - Simulation Methods For Stochastic Systems - Spring 2018 - Graduate Coursework at USC - Dr. Osonde A. Osoba

Statistics library for Dart

EM learning for a mixture of K multivariate Bernoullis with binary images

Leveling Candy Crush Episode's difficulty using Bernoulli principles

C Programming Solutions for Real Analysis and Numerical Analysis Problems

Welcome to the Statistics repository! Here, you'll find files that cover various statistical topics. The repository is organized into different categories to help you navigate through the content!

This repository has been created to complete an assignment given by datainsightonline.com. This assignment is a part of Data Insight | Data Science Program 2021.

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Raku package for statistical distributions and related random variates generations.

Image colorization with a Multivariate Bernoulli Mixture Density network.

Data distribution is a function that lists out all possible values the Data can take. It can be a continuous or discrete Data distribution. Several known standard Probability Distribution functions provide probabilities of occurrence of different possible outcomes in an experiment.

Write a program (in your favorite language) to obtain N samples from each of the following distributions: (i) Bernoulli with μ = 0.5; (ii) Poisson with parameter λ = 5; and (iii) Uniform on [0, 10].

Artificial Intelligence Project aueb Winter 2019

Learned as a part of CS230 course

Used data of emails being spam or non-spam for performing text classification using different probability distributions. Used NLTK library to remove stop words, non-alphabetic characters, and for tokenizing the text. Calculated mean and variance and other params for each word based on the label(spam or ham).

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Teme Probabilitati si Statistica (PS), Anul 2, Semestrul 1, Facultatea de Matematica si Informatica, Universitatea din Bucuresti

Project for the course of Performance Evaluation of Computer Systems and Networks (2023)

Project Probabilistic Programming (PP), MSc Artificial Intelligence, Year 1, Semester 1, Faculty of Mathematics and Computer Science, University of Bucharest

Solutions to problems using Beroulli Trials, Poisson Distribution, Inverse transform method, Accept Reject Sampling and some Comparisons

Using the Bernoulli distribution this terminal app works by passing arguments for the total instance count, positive instances out of those total ones, positive variants, total variants.

This repository contains simulation files of important discrete random variables in MATLAB.

Used data of emails being spam or non-spam for performing text classification using different probability distributions. Used NLTK library to remove stop words, non-alphabetic characters, and for tokenizing the text. Calculated mean and variance and other params for each word based on the label(spam or ham).