Effective Deep Learning Resources: A Shortlist

Jessica YungArtificial Intelligence, Data Science, Education, Machine Learning, StudyingLeave a Comment

A lot of people ask me how to get started with deep learning. In this post I’ve listed a few resources I recommend for getting started. I’ve only chosen a few because I’ve found precise recommendations to be more helpful. Let me know if you have any comments or suggestions! Prelude: If you’re new to machine learning Deep learning is … Read More

AlphaGo Zero: An overview of the algorithm

Jessica YungArtificial Intelligence, Highlights

In this post I go through the algorithms presented in the groundbreaking AlphaGo Zero paper using pseudocode. The objective is to provide a high-level idea of what the model does. Why AlphaGo Zero matters Last week, Google DeepMind published their final iteration of AlphaGo, AlphaGo Zero. To say its performance is remarkable is an understatement. AlphaGo Zero made two breakthroughs: … Read More

Self-Driving Car Engineer Nanodegree Term 1 Review

Jessica YungCareers, Self-Driving Car ND

Many people have asked me what I think about Udacity’s Self-Driving Car Engineer Nanodegree (SDCND). This review aims to help you make a decision as to whether or not to enrol in the first term of Udacity’s SDCND. In short, I think that if you are considering it because you want to work in the self-driving car industry and you … Read More

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

Jessica YungProgramming, Uncategorized

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