from tensorflow import koras

from loras inport layers

from koraci.datasets inport fashion$\_$snist

import matplot$1$ib$.$pyplot as plt

$[13]$: $($traLn$\_$inagos, traLn$\_1$abels$),($test$\_$irages, test$\_$labels$)=$ fashion$\_$Eenist$\_$load$\_$data$()$

$[14]$: train$\_$shape $=$ train$\_$inages.shape

train$\_$Inagers. shape

$[14]$: $(60000,28,28)$

$[15]$: nares $=[\text{'}$T$-$slirt$/$top$\text{'},$'Trouser', 'Vullower','Oress', 'Coat','Sanda$1\text{'},$ 'Shirt', 'Snoaker', 'Bag', 'Ankle boat'$]$

$[15]$: def show$\_$Imapo$[$i$=)$:plt$.$show$()$

$[17]$:

def show$\_$Leage$\_1$abo$1(10,$ value, nanes$)$:plt$.$show$()[18]$:

def show$\_$Isage$\_$vpp$($in$,$ value, prediction, probalility$)$:plt$.$ show$()$prInt$("$The predictod value is $",$nanes$[$prodiction$],"$ with probabL$1$ity: $",$probability$)$

$[19]$: ashow$\_$Leage$\_$LobeL$($test$\_\_$Enges $[28],$ test$\_$LabeLS$[28],$ names$)[97$: def LuI$1$d$\_$mode$1($Irput$\_$shape$)$:Define a fonction to trais a model

$[18]$:

def train$\_$mode$1($rodel$,$ train$\_$tensors,traln$\_1$abels,nb$\_$epochs$)$:rode$1.$fIt$($train$\_$tensor's, train$\_1$abels, epochs$=$ob$\_$epochs$)$

Define a function to predict the fashion type and the probability of the prediction

$[11]$: def prodict$($model$,$test$\_$tersors$)$:

Define the training and validation tersors

Bulld the rodel

in print a sumary of the nodel

if trais the rodel

an evaluate hom good the model is on the testing data

# get the predictions and their probabilites on the testing data set

an show the first $10$ test inages and their predictions with prababilities

af coepute the nanber of wrong predictions

an show the first $10$ testing images with a wrong prediction