www.bharathkreddy.com

Material for Week 10 of ML boot camp.

Prerequisites - you should be familiar and should at least be able to understand below, if not please refer to previous vidoes and course material.

Data wrangling with numpy and pandas, Data viz with matplotlib and seaborn.

Able to handle missing values, categorical data, create pipelines.

Understand Linear regression, Logistic regression, KNN, Naive Bayes. Deploy these algorithms and measure their performance.

YOUR CHECKLIST FOR SESSION ON 24th OCT @ 13:30 PM IST

Day1: Watch all the Videos below.
Day2: Recreate the notebook I discussed in videos. You can find Iris notebook here and Glass notebook here. Work out Titanic, Pima Indian, Car , Iris and credit card datasets on all the algorithms you have learnt. Compare the accuracy scores.
Day3: Do an end to end project - Read data, clean data, use pipelines, measure accuracy for all the algorithms you have learnt so far.
Day4: Read material on Decision trees from internet.
Day5: PRACTICE NOTEBOOKS

SLIDE DECK CART

VIDEOS

1.

INTUTION FOR CART AND DECISION TREES

2.

INTUTION ON GINI IMPURITY

3.

WHY DECISION TREES OVERFIT AND HOW TO FIX IT

4.

HANDS ON EXAMPLE ON JUPYTER NOTEBOOK

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