Behavioural Cloning: Tips for Tackling Project 3

Jessica YungSelf-Driving Car NDLeave a Comment

In this post I list tips that may be helpful for tackling Project 3 of Udacity’s Self-Driving Car Nanodegree, in which you train a neural network to drive a car in a simulator. The neural network learns from data of humans driving the car through the simulator, hence the project name ‘Behavioural Cloning’ – it’s trying to imitate the way … Read More

Bugger! 4.2: Semicircle lane lines

Jessica YungProgramming, Self-Driving Car NDLeave a Comment

Recap from the¬†previous post: we’re trying to trace lane lines from a video. We just dealt with our pipeline spitting out zebra stripes, but now we’ve got a semicircle trace to deal with (see feature image above). What to do? Step 1: Plot intermediate steps to locate the bug Recall that our model is supposed to: Un-distort the test image … Read More

Bugger! Detecting Lane Lines

Jessica YungArtificial Intelligence, Highlights, Self-Driving Car ND3 Comments

This week I’ve been working on the first project of Udacity’s Self Driving Car Engineer Nanodegree – annotating lane lines in images and videos recorded from a front-facing camera mounted on the front of a car. There are plenty of blog posts floating around explaining the concepts (here’s my project code with a walkthrough of the process of annotating images), … Read More

Multi-label classification: One debating topic, many categories

Jessica YungData ScienceLeave a Comment

one-rainbow-many-colours

What colour is this rainbow? Yesterday we wrangled debating motions data using Google Sheets. Today we’ll discuss building a machine learning model to classify these debating topics (e.g. This House Would Break Up the Eurozone) into categories (e.g. ‘Economics’ and ‘International Relations’). Why is this problem interesting? It is primarily a text classification problem. It is a multi-label classification problem. … Read More