Self driving cars: From beginner to advanced (Part 1) — Introduction

Source: Deep Learning on Medium

Recently, I have come across many people asking me about computer vision and self driving cars and various online MOOC that address the same topic. You have many options available like AppliedAI course which is a pretty exhaustive course for DS and AI, Coursera has its own self driving cars module offered by university of Toronto. But I would say that Udacity’s SDCE is a lot more specific, to the point and has various projects which gives students a hands on experience on how a self driving car is built and how your code is integrated into an actual self driving car.

The main motto behind this series is to learn how to build a self driving car myself and convey that knowledge to all the interested researchers, engineers and all the others who are interested in this world of computer vision and self driving cars so that they can benefit from it.

This series is divided into 3 parts with each part consisting of around 12–15 blog posts. In a nutshell, it will be a detailed series and we will be learning everything in details from scratch. The 3 parts of the series are as follows:

  1. Computer vision and deep learning
  2. Sensor fusion and localization
  3. Path planning, control and system integration

I will try to publish 1–2 blogs per week for the next couple of months or probably more. So lets get started with the Part 1–1st blog post