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

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
Viktoria Maksymiuk
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
A Lightweight Hyperparameter Optimization Tool 🚀

The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machine Learning Experiment (MLE) pipeline.

Robert Lange 137 Dec 02, 2022
Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters

Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters. It also works with any regressor compatible with the scikit-learn API (pipelines, CatBoost, LightGBM

Joaquín Amat Rodrigo 297 Jan 09, 2023
Factorization machines in python

Factorization Machines in Python This is a python implementation of Factorization Machines [1]. This uses stochastic gradient descent with adaptive re

Corey Lynch 892 Jan 03, 2023
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

Microsoft 8.4k Dec 30, 2022
BudouX is the successor to Budou, the machine learning powered line break organizer tool.

BudouX Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning powered line break organizer tool. It is standalone

Google 868 Jan 05, 2023
🎛 Distributed machine learning made simple.

🎛 lazycluster Distributed machine learning made simple. Use your preferred distributed ML framework like a lazy engineer. Getting Started • Highlight

Machine Learning Tooling 44 Nov 27, 2022
Esse é o meu primeiro repo tratando de fim a fim, uma pipeline de dados abertos do governo brasileiro relacionado a compras de contrato e cronogramas anuais com spark, em pyspark e SQL!

Olá! Esse é o meu primeiro repo tratando de fim a fim, uma pipeline de dados abertos do governo brasileiro relacionado a compras de contrato e cronogr

Henrique de Paula 10 Apr 04, 2022
Python bindings for MPI

MPI for Python Overview Welcome to MPI for Python. This package provides Python bindings for the Message Passing Interface (MPI) standard. It is imple

MPI for Python 604 Dec 29, 2022
A game theoretic approach to explain the output of any machine learning model.

SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo

Scott Lundberg 18.2k Jan 02, 2023
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
database for artificial intelligence/machine learning data

AIDB v0.0.1 database for artificial intelligence/machine learning data Overview aidb is a database designed for large dataset for machine learning pro

Aarush Gupta 1 Oct 24, 2021
PyTorch extensions for high performance and large scale training.

Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext

Facebook Research 2k Dec 28, 2022
ETNA – time series forecasting framework

ETNA Time Series Library Predict your time series the easiest way Homepage | Documentation | Tutorials | Contribution Guide | Release Notes ETNA is an

Tinkoff.AI 675 Jan 08, 2023
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and many other libraries. Documenta

2.5k Jan 07, 2023
using Machine Learning Algorithm to classification AppleStore application

AppleStore-classification-with-Machine-learning-Algo- using Machine Learning Algorithm to classification AppleStore application. the first step : 1: p

Mohammed Hussien 2 May 02, 2022
Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.

Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage

1.3k Jan 08, 2023
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber

Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber

EconML/CausalML KDD 2021 Tutorial 124 Dec 28, 2022
Dual Adaptive Sampling for Machine Learning Interatomic potential.

DAS Dual Adaptive Sampling for Machine Learning Interatomic potential. How to cite If you use this code in your research, please cite this using: Hong

6 Jul 06, 2022
MLflow App Using React, Hooks, RabbitMQ, FastAPI Server, Celery, Microservices

Katana ML Skipper This is a simple and flexible ML workflow engine. It helps to orchestrate events across a set of microservices and create executable

Tom Xu 8 Nov 17, 2022