Project Description

The task is to develop and apply three$/$or four $($depending on the number of students in the

group$)$ different machine learning algorithms $($one of them must be Artificial Neural Network$).$

Then, show a comparison between all models results that you get. Use everything you learn in

the course. Please give us at least one interesting information you found in your work.

Tasks:

$1-$ Read the dataset.

$2-$ Explore the dataset.

$3-$ Make any fix or replaces in the data $($if needed$).$

$4-$ Make any normalization $($if needed$).$

$5-$ Split the dataset.

$6-$ Apply machine learning algorithms

$7-$ Make any tuning to improve the results $($if possible$).$

$8-$ Compare results

Female Diabetes dataset contains $768$ records. It has $8$ features and one label for each record as

described below:

$1-$ Number of times pregnant

$2-$ Plasma glucose concentration a $2$ hours in an oral glucose tolerance test

$3-$ Diastolic blood pressure $($mm Hg$)$

$4-$ Triceps skin fold thickness $($mm$)$

$5-2-$Hour serum insulin $($mu U$/$ml$)$

$6-$ Body mass index $($weight in kg$/($height in m$)^2)$

$7-$ Diabetes pedigree function

$8-$ Age $($years$)$

$9-$ Class variable $(0\{$has diabetes$\}$ or $1\{$has not diabetes$\})$