Python module for data science and machine learning users.

Overview

dsnk-distributions package

dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calculation complexity.

Files

  • Gaussian distribution for calculating and visualizing a Gaussian distribution. calculation and representation of mean value, and standard deviation of the distribution. Output a histogram of the instance variable data using matplotlib pyplot library.
  • Binomial distribution for calculating and visualizing a Binomial distribution. Inherit functionality from Gaussian distribution with addition of represnting probability of an event occuring n (int) number of trials.

  • Generic distribution class for calculating and visualizing a probability distribution. It performs its functions with help of Binomial distribution and Gaussian distribution.

User installation

The easiest way to install dsnk_distribution is using pip

    pip install dsnk_distribution

or conda:

    conda install dsnk_distribution
Source code

You can check the latest sources with the command:

git clone https://github.com/Emmanuel262/dnsk_distribution.git

Development

The project began after learning the fundamentals of data science and machine learning, and volunteers will soon be needed to help enhance the project's performance and efficiency, as the tasks to be improved will be posted soon.

You might also like...
CD) in machine learning projectsImplementing continuous integration & delivery (CI/CD) in machine learning projects

CML with cloud compute This repository contains a sample project using CML with Terraform (via the cml-runner function) to launch an AWS EC2 instance

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

A library of extension and helper modules for Python's data analysis and machine learning libraries.
A library of extension and helper modules for Python's data analysis and machine learning libraries.

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc

Python module for performing linear regression for data with measurement errors and intrinsic scatter
Python module for performing linear regression for data with measurement errors and intrinsic scatter

Linear regression for data with measurement errors and intrinsic scatter (BCES) Python module for performing robust linear regression on (X,Y) data po

Apache Liminal is an end-to-end platform for data engineers & scientists, allowing them to build, train and deploy machine learning models in a robust and agile way
Apache Liminal is an end-to-end platform for data engineers & scientists, allowing them to build, train and deploy machine learning models in a robust and agile way

Apache Liminals goal is to operationalise the machine learning process, allowing data scientists to quickly transition from a successful experiment to an automated pipeline of model training, validation, deployment and inference in production. Liminal provides a Domain Specific Language to build ML workflows on top of Apache Airflow.

Python package for machine learning for healthcare using a OMOP common data model

This library was developed in order to facilitate rapid prototyping in Python of predictive machine-learning models using longitudinal medical data from an OMOP CDM-standard database.

Python Automated Machine Learning library for tabular data.
Python Automated Machine Learning library for tabular data.

Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie

A toolkit for making real world machine learning and data analysis applications in C++

dlib C++ library Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real worl

Meerkat provides fast and flexible data structures for working with complex machine learning datasets.
Meerkat provides fast and flexible data structures for working with complex machine learning datasets.

Meerkat makes it easier for ML practitioners to interact with high-dimensional, multi-modal data. It provides simple abstractions for data inspection, model evaluation and model training supported by efficient and robust IO under the hood.

Owner
Emmanuel ASIFIWE
Emmanuel ASIFIWE
Data Version Control or DVC is an open-source tool for data science and machine learning projects

Continuous Machine Learning project integration with DVC Data Version Control or DVC is an open-source tool for data science and machine learning proj

Azaria Gebremichael 2 Jul 29, 2021
A collection of neat and practical data science and machine learning projects

Data Science A collection of neat and practical data science and machine learning projects Explore the docs » Report Bug · Request Feature Table of Co

Will Fong 2 Dec 10, 2021
Primitives for machine learning and data science.

An Open Source Project from the Data to AI Lab, at MIT MLPrimitives Pipelines and primitives for machine learning and data science. Documentation: htt

MLBazaar 65 Dec 29, 2022
Applied Machine Learning for Graduate Program in Computer Science (PPGCC)

Applied Machine Learning for Graduate Program in Computer Science (PPGCC) - Federal University of Santa Catarina

Jônatas Negri Grandini 1 Dec 22, 2021
MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine Learning work with thousands of other users.

The collaboration platform for Machine Learning MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine

MLReef 1.4k Dec 27, 2022
A data preprocessing package for time series data. Design for machine learning and deep learning.

A data preprocessing package for time series data. Design for machine learning and deep learning.

Allen Chiang 152 Jan 7, 2023
Python module for machine learning time series:

seglearn Seglearn is a python package for machine learning time series or sequences. It provides an integrated pipeline for segmentation, feature extr

David Burns 536 Dec 29, 2022
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

Epistasis Lab at UPenn 8.9k Jan 9, 2023
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Augusto Almeida 84 Nov 25, 2022
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

Vowpal Wabbit 8.1k Dec 30, 2022