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
INTUTION FOR CART AND DECISION TREES
INTUTION ON GINI IMPURITY
WHY DECISION TREES OVERFIT AND HOW TO FIX IT
HANDS ON EXAMPLE ON JUPYTER NOTEBOOK
A lot of effort and time goes into making this material and videos. One of the ways you can help and support me is by sharing your thoughts on twitter, subscibing my channel on youtube, liking the videos.