Week8 09th October 2020
www.bharathkreddy.com
Material for Week 8 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.
- Python programming
- Numpy & Pandas
- Visualization using Matplotlib & Seaborn
- Able to work with missing data and categorical data using sklearn pipelines or transformers.
- Be clear with Theory of Linear Regression and Logistic Regression
YOUR CHECKLIST FOR SESSION ON 10th 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: Go through the KNN slide deck and practice this notebook.
- Day2: Recreate this notebook and this notebook
- Day3: Go through the Naive Bayes slide deck, I have explained conditional probability here and practice this notebook and this notebook. Go through the deck on probability if you are not comfortable with probability theory. Watch the vidoes in this order : First Probability theory and then Naive bayes video.
- Day4: Run Logisitic Regression, KNN and Naive Bayes algorithms on Titanic and Pima India diabetes dataset. Compare the accuracy reports, Let’s have a discussion next week on your observations.
- Day5: I have saved over hundred datasets here, try picking a few datasets and see if you can try everything that you have learnt so far on these - missing values , categorical values and then model.
Check out the KNN app i have deployed here