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

Mortality risk prediction for COVID-19 patients using XGBoost models

Mortality risk prediction for COVID-19 patients using XGBoost models Using demographic and lab test data received from the HM Hospitales in Spain, I b

1 Jan 19, 2022

Customers Segmentation with RFM Scores and K-means

Customer Segmentation with RFM Scores and K-means RFM Segmentation table: K-Means Clustering: Business Problem Rule-based customer segmentation machin

5 Aug 10, 2022

Machine-Learning with python (jupyter)

Machine-Learning with python (jupyter) 머신러닝 야학 작심 10일과 쥬피터 노트북 기반 데이터 사이언스 시작 들어가기전 https://nbviewer.org/ 페이지를 통해서 쥬피터 노트북 내용을 볼 수 있다. 위 페이지에서 현재 레포 기

1 Jan 23, 2022

We have a dataset of user performances. The project is to develop a machine learning model that will predict the salaries of baseball players.

Salary-Prediction-with-Machine-Learning 1. Business Problem Can a machine learning project be implemented to estimate the salaries of baseball players

9 Oct 14, 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

CyLP is a Python interface to COIN-OR’s Linear and mixed-integer program solvers (CLP, CBC, and CGL)

CyLP CyLP is a Python interface to COIN-OR’s Linear and mixed-integer program solvers (CLP, CBC, and CGL). CyLP’s unique feature is that you can use i

161 Dec 14, 2022

ML Optimizers from scratch using JAX

Toy implementations of some popular ML optimizers using Python/JAX

38 Jul 29, 2022

A classification model capable of accurately predicting the price of secondhand cars

The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this

2 Sep 13, 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

859 Dec 10, 2022

Bayesian Modeling and Computation in Python

Bayesian Modeling and Computation in Python Open access and Code This repository contains the open access version of the text and the code examples in

339 Jan 02, 2023

Mixing up the Invariant Information clustering architecture, with self supervised concepts from SimCLR and MoCo approaches

Self Supervised clusterer Combined IIC, and Moco architectures, with some SimCLR notions, to get state of the art unsupervised clustering while retain

9 Feb 13, 2022

Self Organising Map (SOM) for clustering of atomistic samples through unsupervised learning.

Self Organising Map for Clustering of Atomistic Samples - V2 Description Self Organising Map (also known as Kohonen Network) implemented in Python for

0 Nov 16, 2021

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

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

1 Jun 27, 2022

monolish: MONOlithic Liner equation Solvers for Highly-parallel architecture

monolish is a linear equation solver library that monolithically fuses variable data type, matrix structures, matrix data format, vendor specific data transfer APIs, and vendor specific numerical alg

179 Dec 21, 2022

Lightweight Machine Learning Experiment Logging 📖

Simple logging of statistics, model checkpoints, plots and other objects for your Machine Learning Experiments (MLE). Furthermore, the MLELogger comes with smooth multi-seed result aggregation and co

65 Dec 08, 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.

25 Dec 28, 2022

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

Related tags

Overview

Naive-Bayes Spam Classificator

Main files

How does it work?

Owner

Viktoria Maksymiuk

Mortality risk prediction for COVID-19 patients using XGBoost models

Customers Segmentation with RFM Scores and K-means

Machine-Learning with python (jupyter)

We have a dataset of user performances. The project is to develop a machine learning model that will predict the salaries of baseball players.

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

CyLP is a Python interface to COIN-OR’s Linear and mixed-integer program solvers (CLP, CBC, and CGL)

ML Optimizers from scratch using JAX

A classification model capable of accurately predicting the price of secondhand cars

Coursera Machine Learning - Python code

Bayesian Modeling and Computation in Python

Mixing up the Invariant Information clustering architecture, with self supervised concepts from SimCLR and MoCo approaches

Self Organising Map (SOM) for clustering of atomistic samples through unsupervised learning.

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

monolish: MONOlithic Liner equation Solvers for Highly-parallel architecture

Lightweight Machine Learning Experiment Logging 📖

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.

A benchmark of data-centric tasks from across the machine learning lifecycle.

A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.

Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

slim-python is a package to learn customized scoring systems for decision-making problems.