Simple Machine Learning Tool Kit

Related tags

Machine Learningsmltk
Overview

Getting started

smltk (Simple Machine Learning Tool Kit) package is implemented for helping your work during

  • data preparation
  • testing your model

The goal is to implement this package for each step of machine learning process that can simplify your code.

It is part of the educational repositories to learn how to write stardard code and common uses of the TDD.

Installation

If you want to use this package into your code, you can install by python3-pip:

pip3 install smltk
python3
>>> from smltk.metrics import Metrics
>>> help(Metrics)

The package is not self-consistent. So if you want to contribute, you have to download the package by github and to install the requirements

git clone https://github.com/bilardi/smltk
cd smltk/
pip3 install --upgrade -r requirements.txt

Read the documentation on readthedocs for

  • API
  • Usage
  • Development

Change Log

See CHANGELOG.md for details.

License

This package is released under the MIT license. See LICENSE for details.

Owner
Alessandra Bilardi
Data & Automation Specialist | AWS Enthusiasts | CoderDojo Mentor
Alessandra Bilardi
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets

Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,

Samrat Mitra 2 Nov 18, 2021
This project has Classification and Clustering done Via kNN and K-Means respectfully

This project has Classification and Clustering done Via kNN and K-Means respectfully. It later tests its efficiency via F1/accuracy/recall/precision for kNN and Davies-Bouldin Index for Clustering. T

Mohammad Ali Mustafa 0 Jan 20, 2022
Estudos e projetos feitos com PySpark.

PySpark (Spark com Python) PySpark é uma biblioteca Spark escrita em Python, e seu objetivo é permitir a análise interativa dos dados em um ambiente d

Karinne Cristina 54 Nov 06, 2022
Python library which makes it possible to dynamically mask/anonymize data using JSON string or python dict rules in a PySpark environment.

pyspark-anonymizer Python library which makes it possible to dynamically mask/anonymize data using JSON string or python dict rules in a PySpark envir

6 Jun 30, 2022
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
Book Recommender System Using Sci-kit learn N-neighbours

Model-Based-Recommender-Engine I created a book Recommender System using Sci-kit learn's N-neighbours algorithm for my model and the streamlit library

1 Jan 13, 2022
Made in collaboration with Chris George for Art + ML Spring 2019.

Deepdream Eyes Made in collaboration with Chris George for Art + ML Spring 2019.

Francisco Cabrera 1 Jan 12, 2022
This is the code repository for Interpretable Machine Learning with Python, published by Packt.

Interpretable Machine Learning with Python, published by Packt

Packt 299 Jan 02, 2023
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

152 Jan 02, 2023
Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information.

Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information.

Priyansh Sharma 7 Nov 09, 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
Open-Source CI/CD platform for ML teams. Deliver ML products, better & faster. ⚡️🧑‍🔧

Deliver ML products, better & faster Giskard is an Open-Source CI/CD platform for ML teams. Inspect ML models visually from your Python notebook 📗 Re

Giskard 335 Jan 04, 2023
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application

Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).

Philip May 2 Dec 03, 2021
A Microsoft Azure Web App project named Covid 19 Predictor using Machine learning Model

A Microsoft Azure Web App project named Covid 19 Predictor using Machine learning Model (Random Forest Classifier Model ) that helps the user to identify whether someone is showing positive Covid sym

Priyansh Sharma 2 Oct 06, 2022
A quick reference guide to the most commonly used patterns and functions in PySpark SQL

Using PySpark we can process data from Hadoop HDFS, AWS S3, and many file systems. PySpark also is used to process real-time data using Streaming and

Sundar Ramamurthy 53 Dec 21, 2022
A naive Bayes model for cancer classification using a set of documents

Naivebayes text classifcation model for cancer and noncancer documents Author: Alex King Purpose Requirements/files included How to use 1. Purpose The

Alex W King 1 Nov 24, 2021
A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile

matrixprofile-ts matrixprofile-ts is a Python 2 and 3 library for evaluating time series data using the Matrix Profile algorithms developed by the Keo

Target 696 Dec 26, 2022
MLFlow in a Dockercontainer based on Azurite and Postgres

mlflow-azurite-postgres docker This is a MLFLow image which works with a postgres DB and a local Azure Blob Storage Instance (Azurite). This image is

2 May 29, 2022
Gaussian Process Optimization using GPy

End of maintenance for GPyOpt Dear GPyOpt community! We would like to acknowledge the obvious. The core team of GPyOpt has moved on, and over the past

Sheffield Machine Learning Software 847 Dec 19, 2022
Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.

Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.

FINRA 25 Dec 28, 2022