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gimseng / 99-ML-Learning-Projects

A list of 99 machine learning projects for anyone interested to learn from coding and building projects
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[EXE] Implementing naive bayes algorithm from scratch #100

Closed AayushK47 closed 3 years ago

AayushK47 commented 3 years ago

Learning Goals

Naive Bayes algorithm is one of the most simplest yet powerful ML algorithm out there, often used as a baseline for text based classification. Understanding the working of this algorithm will help in understanding:-

Exercise Statement

[Explain and describe what the exercise is] The objective of this exercise is to implement the Naive Bayes algorithm along with using python 3 and numpy. The dataset to be used is Haberman's Survival Dataset

Prerequisites

You must have the basic understanding of what machine learning is, what is supervised and unsupervised learning, what is classification, etc. Knowledge of python 3 and numpy if also required.

Data source/summary:

Haberman's Survival Dataset is a dataset containing cases from a study that was conducted between 1958 and 1970 at the University of Chicago's Billings Hospital on the survival of patients who had undergone surgery for breast cancer. Click here to learn more about this dataset.

Further Links:

gimseng commented 3 years ago

Great idea @AayushK47 ! If you already have some codes available to get started, feel free to check out our previous projects and contributing guidelines to see how we structure things here.

glitch401 commented 3 years ago

Greetings, could i get started with this issue ?

gimseng commented 3 years ago

Hi @glitch401 it seems like PR #113 has been submitted to address this. Perhaps you could follow the PR thread there, and if @glitch401 needs some help, maybe you could assist on that.