# Week7 03rd October 2020

# www.bharathkreddy.com

## Material for Week 7 of ML boot camp.

Prerequisites - you should be familiar and should at least be able to understand below

- Numpy
- Pandas
- Matplotlib
- Able to use sklearn to split the dataset in test and train datasets
- Able to use sklearn to pre-preocess the data and use sklearn pipelines
- Be clear with Theory of Linear Regression and be able to Use Linear Regression

### YOUR CHECKLIST FOR SESSION ON 03rd OCT @ 13:30 PM IST

Items ticked are highly recomended to be completed before session, unticked ones are for the more adventerous of you :)

- Day1: Understand working with missing data AND Practice working on missing data
- Day2: Working with categorical data and Three practice datasets
- Day3: Use Pipelines to manage Missing values & categorical encoding at one go using SKLEARN PIPELINES, I am not adding any separate practice datasets as you can practice these concepts on same notebooks which i have provided for Linear Regression and Logistic Regression.
- Day4: Linear Regression: First go through this notebook. Then go through 2 notebooks I provided in week5. You can use Ames housing & Boston housing datasets to predict Prices.These datasets are from Missing value day1 link. You can use Automobile import dataset from day2 link to predict Prices of automobiles.
- Day5: Logistic Regression revise week6, Practice you skills on Titanic dataset to predict survival, Pima-Indian dataset to predict diabites.