MACHINE LEARNING LECTURE PROJECTa$)$ Find a dataset from Internet with at least $10\mathrm{.}000$ data in it$.$ Kaggle UCI Machine Learning Repository Google Dataset Search: CMU Libraries:$$Discover high$-$quality datasets thanks to the collection of Huajin Wang, at CMU$$b$)$ Show related information about the dataset. $($How many records does it have? What are the features? Types of the features?.... etc.$)$ Dataset should contain at least $15$ features in it$.$DATASET NAME :DATASET WEB LINK :DATASET INFOHow many records does it containsHow many features does it haveHow many different classes exist in the dataset?What are number of examples for each classes?How many NULL values exist? $($depending on the featuresdistinctly$)$Which features are not numeric?$$c$)$ Use Label Encoding for at least one of the features$($Explain your reason why do make this operation?$)$d$)$ Use One Hot encoding for at least one of the features $($Explain your reason why do make this operation?$)$ e$)$ Analyze the Missing Valuesa. Delete some columns $($Explain your reason why do make this operation?$)$ b$.$ Delete some rows $($Explain your reason why do make this operation?$)$c$.$ Impute some missing data $($Explain your reason why do make this operation?$)$f$)$ Find the best correlated Features in the Dataset g$)$ Execute a Normalization$/$Scaling in the Dataset h$)$ Train your new dataset at least $5$ different Machine Learning algorithms$$i$)$ Use $5-$fold approach to measure the performance of the systemWITH A RANDOM SELECTION WE REACHED THE FOLLOWING RESULTS$*****$WITH $5-$FOLD APPROACH I REACHED THE FOLLOWING RESULT$$j$)$ Put their results to a table to make a comparison$$k$)$ Calculate the training time for all of theml$)$ Select the best $10$ features from the databaseSHOW THE LIST OF THE FEATURES$$m$)$ Write a Conference paper to Show all your reached results.