Accelerating model creation and evaluation.

Related tags

Machine Learningpythondata-sciencemachine-learning
Overview

Emerald

EmeraldML

A machine learning library for streamlining the process of
(1) cleaning and splitting data,
(2) training, optimizing, and testing various models based on the task, and
(3) scoring and ranking them
during the exploratory phase for an elementary analysis of which models perform better for a specific dataset.

Installation

Dependencies

  • Python (>= 3.7)
  • NumPy (>= 1.21.2)
  • pandas (>= 1.3.3)
  • scikit-learn (>= 0.24.2)
  • statsmodels (>= 0.12.2)

User installation

pip install emeraldml

Development

Source code

You can check the latest sources with the command:

git clone https://github.com/yu3ufff/emeraldml.git

Demo

Getting the data:

import pandas as pd
audi = pd.read_csv('audi.csv')
audi.head()
|    | model   |   year |   price | transmission   |   mileage | fuelType   |   tax |   mpg |   engineSize |
|---:|:--------|-------:|--------:|:---------------|----------:|:-----------|------:|------:|-------------:|
|  0 | A1      |   2017 |   12500 | Manual         |     15735 | Petrol     |   150 |  55.4 |          1.4 |
|  1 | A6      |   2016 |   16500 | Automatic      |     36203 | Diesel     |    20 |  64.2 |          2   |
|  2 | A1      |   2016 |   11000 | Manual         |     29946 | Petrol     |    30 |  55.4 |          1.4 |
|  3 | A4      |   2017 |   16800 | Automatic      |     25952 | Diesel     |   145 |  67.3 |          2   |
|  4 | A3      |   2019 |   17300 | Manual         |      1998 | Petrol     |   145 |  49.6 |          1   |

Using EmeraldML:

import emerald
from emerald.boa import RegressionBoa

rboa = RegressionBoa(random_state=3)
rboa.hunt(data=audi, target='price')
rboa.ladder
[(OptimalRFRegressor, 0.9624889664024406),
 (OptimalDTRegressor, 0.9514992411732952),
 (OptimalKNRegressor, 0.9511411883559433),
 (OptimalLinearRegression, 0.8876961846248467),
 (OptimalABRegressor, 0.8491539140007975)]

for i in range(len(rboa)):
    print(rboa.model(i))
RandomForestRegressor(min_samples_split=5, n_estimators=500, random_state=3)
DecisionTreeRegressor(max_depth=15, min_samples_split=10, random_state=3)
KNeighborsRegressor(n_neighbors=3, p=1)
LinearRegression()
AdaBoostRegressor(learning_rate=0.1, n_estimators=100, random_state=3)
Owner
Yusuf
Yusuf
GitHub Repository
Polyglot Machine Learning example for scraping similar news articles.

Polyglot Machine Learning example for scraping similar news articles In this example, we will see how we can work with Machine Learning applications w

MetaCall 15 Mar 28, 2022
Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.

sklearn-evaluation Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking, and Jupyter notebook analysis. Suppo

Eduardo Blancas 354 Dec 31, 2022
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class

Tamas Madl 482 Nov 19, 2022
Coursera Machine Learning - Python code

Coursera Machine Learning This repository contains python implementations of certain exercises from the course by Andrew Ng. For a number of assignmen

Jordi Warmenhoven 859 Dec 10, 2022
Learn how to responsibly deliver value with ML.

Made With ML Applied ML · MLOps · Production Join 30K+ developers in learning how to responsibly deliver value with ML. 🔥 Among the top MLOps reposit

Goku Mohandas 32k Dec 30, 2022
This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch

This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment to test the algorithm

Martin Huber 59 Dec 09, 2022
A machine learning model for Covid case prediction

CovidcasePrediction A machine learning model for Covid case prediction Problem Statement Using regression algorithms we can able to track the active c

VijayAadhithya2019rit 1 Feb 02, 2022
MooGBT is a library for Multi-objective optimization in Gradient Boosted Trees.

MooGBT is a library for Multi-objective optimization in Gradient Boosted Trees. MooGBT optimizes for multiple objectives by defining constraints on sub-objective(s) along with a primary objective. Th

Swiggy 66 Dec 06, 2022
Practical Time-Series Analysis, published by Packt

Practical Time-Series Analysis This is the code repository for Practical Time-Series Analysis, published by Packt. It contains all the supporting proj

Packt 325 Dec 23, 2022
This project used bitcoin, S&P500, and gold to construct an investment portfolio that aimed to minimize risk by minimizing variance.

minvar_invest_portfolio This project used bitcoin, S&P500, and gold to construct an investment portfolio that aimed to minimize risk by minimizing var

1 Jan 06, 2022
Pyomo is an object-oriented algebraic modeling language in Python for structured optimization problems.

Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models. Pyomo can be used to define symbolic p

Pyomo 1.4k Dec 28, 2022
A machine learning web application for binary classification using streamlit

Machine Learning web App This is a machine learning web application for binary classification using streamlit options this application contains 3 clas

abdelhak mokri 1 Dec 20, 2021
Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning

Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning

Felix Daudi 1 Jan 06, 2022
Markov bot - A Writing bot based on Markov Chain for Data Structure Lab

基于马尔可夫链的写作机器人 前端 用html/css完成 Demo展示（已给出文本的相应展示） 用户提供相关的语料库后训练的成果 后端 要完成的几个接口 解析文

DysprosiumDy 9 May 05, 2022
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.

Sontag Lab 75 Jan 03, 2023
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning

Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning

Microsoft 43.4k Jan 04, 2023
Uplift modeling and causal inference with machine learning algorithms

Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang

Uber Open Source 3.7k Jan 07, 2023
Kalman filter library

The kalman filter framework described here is an incredibly powerful tool for any optimization problem, but particularly for visual odometry, sensor fusion localization or SLAM.

comma.ai 276 Jan 01, 2023
🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code

Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co

Hugging Face 2.5k Jan 07, 2023
Lseng-iseng eksplor Machine Learning dengan menggunakan library Scikit-Learn

Kalo dengar istilah ML, biasanya rada ambigu. Soalnya punya beberapa kepanjangan, seperti Mobile Legend, Makan Lontong, Ma**ng L*v* dan lain-lain. Tapi pada repo ini membahas Machine Learning :)

Alfiyanto Kondolele 1 Apr 06, 2022