Learned as a part of CS230 course

Artificial Intelligence Project aueb Winter 2019

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.

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).

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].

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

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

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.

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

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).

C Programming Solutions for Real Analysis and Numerical Analysis Problems

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.

Image colorization with a Multivariate Bernoulli Mixture Density network.

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

Statistics library for Dart

Leveling Candy Crush Episode's difficulty using Bernoulli principles

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

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