Gaussian and Binomial distributions Python Package for Machine Learning and Data Science

neha_probability_distribution

neha_probability_distribution is a Python module/package for Machine Learning and Data Science built for Gaussian and Binomial distributions. This package is distributed under the MIT License.

Installation.

To install simply run(Commandline);

pip install neha-probability-distribution

conda install neha-probability-distribution

PyPI link: https://pypi.org/manage/project/neha-probability-distribution/

Testing.

pip install -i https://test.pypi.org/simple/ neha-probability-distribution/

TestPyPI link: https://test.pypi.org/project/neha-probability-distribution/

Sample python test code.

On your commandline run below python code after installation.

>>> from distributions_gauss_bi import Gaussian, Binomial
>>> Gaussian(38,17)
>>> Binomial(0.4, 35)

Gaussian and Binomial distribution overview

1. Gaussian distribution (also known as Normal distribution)

In probability theory, a normal distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution; and is its standard deviation.

2. Binomial distribution.

In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes in a sequence of n independent experiments, each asking a yes–no question, and each with its own boolean-valued outcome: success/yes/true/one (with probability p) or failure/no/false/zero (with probability q = 1 − p).

Further Resources.

If you would like to review the Gaussian (normal) distribution and binomial distribution, here are a few resources:

nehakalbande/neha_probability_distribution