Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm.

Last update: Jun 27, 2022

Related tags

Overview

Naive-Bayes Spam Classificator

Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm. Main goal is to code a spam filter from scratch that classifies messages with an accuracy greater than 90%.

Main files

This project contains 2 modules:

bayesian_classifier.py -- BayesianClassifier class which is used to classify whether the message is spam or ham. It also calculates model score for accuracy.
main.py -- main file for running the programm.

How does it work?

After running a program, Spam Classificator provides the user with 2 options:

to test a model on data base and get model score;
to test a model on statement the user inputs;

If there are many words in the statement that are not present in the database, then the program will most likely output ‘needs human classification, probably spam’.

Owner

Viktoria Maksymiuk

GitHub Repository

A Python library for choreographing your machine learning research.

270 Jan 06, 2023

Cohort Intelligence used to solve various mathematical functions

Cohort-Intelligence-for-Mathematical-Functions About Cohort Intelligence : Cohort Intelligence ( CI ) is an optimization technique. It attempts to mod

2 Oct 25, 2021

Exemplary lightweight and ready-to-deploy machine learning project

6 Dec 20, 2022

Spark development environment for k8s

Local Spark Dev Env with Docker Development environment for k8s. Using the spark-operator image to ensure it will be the same environment. Start conta

18 Jan 04, 2022

Data Efficient Decision Making

197 Jan 06, 2023

Xeasy-ml is a packaged machine learning framework.

xeasy-ml 1. What is xeasy-ml Xeasy-ml is a packaged machine learning framework. It allows a beginner to quickly build a machine learning model and use

9 Mar 14, 2022

Distributed scikit-learn meta-estimators in PySpark

sk-dist: Distributed scikit-learn meta-estimators in PySpark What is it? sk-dist is a Python package for machine learning built on top of scikit-learn

282 Dec 09, 2022

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

115 Dec 12, 2022

Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice

Responsible AI Workshop Responsible innovation is top of mind. As such, the tech industry as well as a growing number of organizations of all kinds in

9 Sep 14, 2022

K-Means clusternig example with Python and Scikit-learn

Unsupervised-Machine-Learning Flat Clustering K-Means clusternig example with Python and Scikit-learn Flat clustering Clustering algorithms group a se

1 Dec 13, 2021

Lingtrain Alignment Studio is an ML based app for texts alignment on different languages.

Lingtrain Alignment Studio Intro Lingtrain Alignment Studio is the ML based app for accurate texts alignment on different languages. Extracts parallel

186 Jan 03, 2023

A simple example of ML classification, cross validation, and visualization of feature importances

Simple-Classifier This is a basic example of how to use several different libraries for classification and ensembling, mostly with sklearn. Example as

2 Aug 25, 2022

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas

1.6k Dec 31, 2022

A simple machine learning python sign language detection project.

SST Coursework 2022 About the app A python application that utilises the tensorflow object detection algorithm to achieve automatic detection of ameri

2 Jun 30, 2022

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, validat

121 Dec 28, 2022