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
LibTraffic is a unified, flexible and comprehensive traffic prediction library based on PyTorch

LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is imp

432 Jan 05, 2023
A concept I came up which ditches the idea of "layers" in a neural network.

Dynet A concept I came up which ditches the idea of "layers" in a neural network. Install Copy Dynet.py to your project. Run the example Install matpl

Anik Patel 4 Dec 05, 2021
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
Machine-learning-dell - Repositório com as atividades desenvolvidas no curso de Machine Learning

📚 Descrição Neste curso da Dell aprofundamos nossos conhecimentos em Machine Learning. 🖥️ Aulas (Em curso) 1.1 - Python aplicado a Data Science 1.2

Claudia dos Anjos 1 Jan 05, 2022
A machine learning toolkit dedicated to time-series data

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

2.3k Jan 05, 2023
TIANCHI Purchase Redemption Forecast Challenge

TIANCHI Purchase Redemption Forecast Challenge

Haorui HE 4 Aug 26, 2022
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

Sebastian Raschka 4.2k Dec 29, 2022
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
This repo implements a Topological SLAM: Deep Visual Odometry with Long Term Place Recognition (Loop Closure Detection)

This repo implements a topological SLAM system. Deep Visual Odometry (DF-VO) and Visual Place Recognition are combined to form the topological SLAM system.

Best of Australian Centre for Robotic Vision (ACRV) 32 Jun 23, 2022
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
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
Time series forecasting with PyTorch

Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time

Jan Beitner 2.5k Jan 02, 2023
XGBoost + Optuna

AutoXGB XGBoost + Optuna: no brainer auto train xgboost directly from CSV files auto tune xgboost using optuna auto serve best xgboot model using fast

abhishek thakur 517 Dec 31, 2022
Python ML pipeline that showcases mltrace functionality.

mltrace tutorial Date: October 2021 This tutorial builds a training and testing pipeline for a toy ML prediction problem: to predict whether a passeng

Log Labs 28 Nov 09, 2022
MLBox is a powerful Automated Machine Learning python library.

MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle

Axel 1.4k Jan 06, 2023
dirty_cat is a Python module for machine-learning on dirty categorical variables.

dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.

637 Dec 29, 2022
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
This repo includes some graph-based CTR prediction models and other representative baselines.

Graph-based CTR prediction This is a repository designed for graph-based CTR prediction methods, it includes our graph-based CTR prediction methods: F

Big Data and Multi-modal Computing Group, CRIPAC 47 Dec 30, 2022
onelearn: Online learning in Python

onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o

15 Nov 06, 2022
Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Microsoft 366 Jan 03, 2023