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CMPE-255-Assignment-1

a) Pick a kaggle data set which might be fairly noisy (Eg: https://analyticsindiamag.com/10-datasets-for-data-cleaning-practice-for-beginners/ (Links to an external site.) or more)

b) write a data cleaning and preprocessing and visualization colab using any data set - you can find few from kaggle etc...

c) you can do model training with scikit learn as well but we will not check the accuracy/performance of the model. the main focus is whether you did the right data cleaning

Please try to use a number of techniques in there and do comprehensive cleaning and pre processing. write colab with great comments and description

please submit the colab and a read.me in github folder - provide the url of github folder (with full public access)

Try to combine number of techniques in leaderboard members of kaggle for data cleaning if possible.

Have Choosen Hotel-Booking dataset from the below link

https://analyticsindiamag.com/10-datasets-for-data-cleaning-practice-for-beginners

Dataset: : https://www.kaggle.com/jessemostipak/hotel-booking-demand

Colab File: Hotel_Booking.ipynb

STEPS FOLLOWED:

1) DOWNLOADING DATASET, INSTALLING & LOADING MODULES FOR ANALYSIS

2) UNDERSTANDING DATA

3) DATA WRANGLING FOR EDA

4) EDA

5) FINDING DATA CORRELATION & DATA PREPROCESSING FOR ML MODEL

6) ML CLASSIFICATION ALGORITHMS ( KNN, LOGISTIC REGRESSION, SVM )

7) ACCURACY COMPARISON OF ALL ML MODELS

Finally, using Google OpenRefine Tool for Data Cleaning operations & data pre-processiong for the same dataset.

Link: https://drive.google.com/file/d/12qINsg-qAsizsBLvOdEj-XeTYqlpUUyN/view?usp=sharing

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