easyNeuron is a simple way to create powerful machine learning models, analyze data and research cutting-edge AI.

Overview


Logo

easyNeuron

Project status badge. GitHub commit activity badge. Lines of code badge. Visits to this repo badge.

easyNeuron is the new, easy way to create, analyze and program machine learning 🧠 models.


Table of Contents 📝




Features

  • Models
    • Linear Regression
    • Logistic Regression
    • Decision Trees
    • Random Forest
    • Adaboost
    • K-Nearest Neighbours
    • K-Means Clustering
    • Neural Networks


History

easyNeuron was created in 2021 by @Neuron-AI, aiming to create an easy experience for all ML engineers, with any and all of the newly developed algorithms from Neuron AI.


Naming Conventions 🧾

Mostly, the names of modules are universal, but, there was some choice of the maths section of the module. In the end, the maths section is known as easyneuron.math rather than easyneuron.maths (as we are a British group), since there is such a large population who'll use this knowing American English, and it is quicker to type the American version anyway.


Contributing

Like 👍 this project? Want to contribute to it? Why not put up a pull request with your code changes on it.

Note: Please read the Contributing Guidelines and the appropriate code style document (linked to in CONTRIBUTING.md).


Project Stats 📈

Stat Badge
Codacy Quality Rating
Owner
Neuron AI
Pushing the boundaries of open source AI.
Neuron AI
ETNA – time series forecasting framework

ETNA Time Series Library Predict your time series the easiest way Homepage | Documentation | Tutorials | Contribution Guide | Release Notes ETNA is an

Tinkoff.AI 675 Jan 08, 2023
A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Oleksii Trekhleb 1.4k Jan 06, 2023
A linear regression model for house price prediction

Linear_Regression_Model A linear regression model for house price prediction. This code is using these packages, so please make sure your have install

ShawnWang 1 Nov 29, 2021
Databricks Certified Associate Spark Developer preparation toolkit to setup single node Standalone Spark Cluster along with material in the form of Jupyter Notebooks.

Databricks Certification Spark Databricks Certified Associate Spark Developer preparation toolkit to setup single node Standalone Spark Cluster along

19 Dec 13, 2022
(3D): LeGO-LOAM, LIO-SAM, and LVI-SAM installation and application

SLAM-application: installation and test (3D): LeGO-LOAM, LIO-SAM, and LVI-SAM Tested on Quadruped robot in Gazebo ● Results: video, video2 Requirement

EungChang-Mason-Lee 203 Dec 26, 2022
All-in-one web-based development environment for machine learning

All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu

3 Feb 03, 2021
A collection of Scikit-Learn compatible time series transformers and tools.

tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p

Chris Santiago 0 Mar 30, 2022
AutoX是一个高效的自动化机器学习工具,它主要针对于表格类型的数据挖掘竞赛。 它的特点包括: 效果出色、简单易用、通用、自动化、灵活。

English | 简体中文 AutoX是什么? AutoX一个高效的自动化机器学习工具,它主要针对于表格类型的数据挖掘竞赛。 它的特点包括: 效果出色: AutoX在多个kaggle数据集上,效果显著优于其他解决方案(见效果对比)。 简单易用: AutoX的接口和sklearn类似,方便上手使用。

4Paradigm 431 Dec 28, 2022
Automated Machine Learning with scikit-learn

auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here

AutoML-Freiburg-Hannover 6.7k Jan 07, 2023
Given the names and grades for each student in a class N of students, store them in a nested list and print the name(s) of any student(s) having the second lowest grade.

Hackerank-Nested-List Given the names and grades for each student in a class N of students, store them in a nested list and print the name(s) of any s

Sangeeth Mathew John 2 Dec 14, 2021
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models. The library is a collection of Keras models

538 Jan 01, 2023
Getting Profit and Loss Make Easy From Binance

Getting Profit and Loss Make Easy From Binance I have been in Binance Automated Trading for some time and have generated a lot of transaction records,

17 Dec 21, 2022
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc)

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed

Chris Yuan 1 Feb 06, 2022
This repository contains the code to predict house price using Linear Regression Method

House-Price-Prediction-Using-Linear-Regression The dataset I used for this personal project is from Kaggle uploaded by aariyan panchal. Link of Datase

0 Jan 28, 2022
A toolbox to iNNvestigate neural networks' predictions!

iNNvestigate neural networks! Table of contents Introduction Installation Usage and Examples More documentation Contributing Releases Introduction In

Maximilian Alber 1.1k Jan 05, 2023
Machine Learning Study 혼자 해보기

Machine Learning Study 혼자 해보기 기여자 (Contributors) ✨ Teddy Lee 🏠 HongJaeKwon 🏠 Seungwoo Han 🏠 Tae Heon Kim 🏠 Steve Kwon 🏠 SW Song 🏠 K1A2 🏠 Wooil

Teddy Lee 1.7k Jan 01, 2023
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

AI Fairness 360 (AIF360) The AI Fairness 360 toolkit is an extensible open-source library containg techniques developed by the research community to h

1.9k Jan 06, 2023
This is the code repository for LRM Stochastic watershed model.

LRM-Squannacook Input data for generating stochastic streamflows are observed and simulated timeseries of streamflow. their format needs to be CSV wit

1 Feb 14, 2022
Fast Fourier Transform-accelerated Interpolation-based t-SNE (FIt-SNE)

FFT-accelerated Interpolation-based t-SNE (FIt-SNE) Introduction t-Stochastic Neighborhood Embedding (t-SNE) is a highly successful method for dimensi

Kluger Lab 547 Dec 21, 2022
Bayesian Additive Regression Trees For Python

BartPy Introduction BartPy is a pure python implementation of the Bayesian additive regressions trees model of Chipman et al [1]. Reasons to use BART

187 Dec 16, 2022