// Databricks notebook source exported at Sat, 18 Jun 2016 23:27:13 UTC

Scalable Data Science

prepared by Raazesh Sainudiin and Sivanand Sivaram

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The html source url of this databricks notebook and its recorded Uji Image of Uji, Dogen's Time-Being :

Let us visit an interactive visual cognitive tool for the basics ideas in linear regression:

http://setosa.io/ev/ordinary-least-squares-regression/

The following video is a very concise and thorough treatment of linear regression for those who have taken the 200-level linear algebra. Others can fully understand it with some effort and revisiting.

Linear Regression by Ameet Talwalkar in BerkeleyX: CS190.1x Scalable Machine Learning

(watch now 11:13):

Ridge regression has a Bayesian interpretation where the weights have a zero-mean Gaussian prior. See 7.5 in Murphy’s Machine Learning: A Probabilistic Perspective for details.

Please take notes in mark-down if you want.

For latex math within markdown you can do the following for in-line maths: \(\mathbf{A}_{i,j} \in \mathbb{R}^1\). And to write maths in display mode do the following:

\[\mathbf{A} \in \mathbb{R}^{m \times d}\]

You will need to write such notes for your final project presentation!