## Getting Started with Kaggle #1: Text Data (Quora question pairs, Spam SMSes)

Jessica YungData Science

Kaggle is a platform for data science competitions and has great people and resources. But how do you get started? It can be overwhelming with so many competitions, data sets and kernels (notebooks where people share their code). One kernel may contain over ten new concepts, so if you’re new to machine learning (or even if you’re not), you may … Read More

## How to Tackle Programming Problems (Google Code Jam 2017 Qualification Round, Problem A)

Jessica Yung

This is a walkthrough of how one might start thinking about Problem A (small input) of Google Code Jam’s 2017 Qualification Round (April 8-9). Google posts excellent solutions to their problems, so the focus here will be that of the idea generation process or how one might begin to tackle such problems. Full problem statements can be found here. Problem A (Oversized … Read More

## What do the Kalman Filter Equations Mean? (Part 2: Update)

Jessica YungSelf-Driving Car ND

In my previous post, I explained the Kalman Filter prediction equations in a big-picture way. In this post I will explain the update equations. The equations to focus on are the last two. (We use the results from the first three equations in the last two equations.) Eqn 1: Updating the object state x: x’ is the predicted object state … Read More

## What do the Kalman Filter Equations mean? (Part 1: Prediction)

Jessica YungSelf-Driving Car ND

In the second term of Udacity’s Self-Driving Car Engineer Nanodegree, you start out learning about Kalman Filters. You are given a bunch of equations. What do they mean? In this post I explain the prediction equations (left) in a big-picture way. I explain the update equations in my next post. Predicting the object state x: Equation: x is the object state. … Read More