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
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
Explaining Tensorflow Code for a Convolutional Neural Network
In this post, we will go through the code for a convolutional neural network. We will use Aymeric Damien’s implementation. I recommend you have a skim before you read this post. I have included the key portions of the code below. If you’re not familiar with TensorFlow or neural networks, you may find it useful to read my post on multilayer … Read More
Explaining TensorFlow code for a Multilayer Perceptron
In this post we go through the code for a multilayer perceptron in TensorFlow. We will use Aymeric Damien’s implementation. I recommend you have a skim before you read this post. I have included the key portions of the code below. 1. Code Here are the relevant network parameters and graph input for context (skim this):
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# Network Parameters n_hidden_1 = 256 # 1st layer number of features n_hidden_2 = 256 # 2nd layer number of features n_input = 784 # MNIST data input (img shape: 28*28) n_classes = 10 # MNIST total classes (0-9 digits) # tf Graph input x = tf.placeholder("float", [None, n_input]) y = tf.placeholder("float", [None, n_classes]) |
Here is the model … Read More
Bugger! Detecting Lane Lines
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
Ian Goodfellow: Generative Adversial Networks
The second talk I went to at AI WithTheBest 2016 was Ian Goodfellow’s talk on Generative Adversarial Networks (GANs), which he invented. Ian is a researcher at OpenAI. GANs are generative models based on supervised learning and game theory. They learn to generate realistic samples and have mostly been used to generate images. For example, you can feed it images … Read More
What data does Facebook.com load?
Today we’re going to look at your Facebook homepage’s source code. This is interesting because it gives you an idea of the data Facebook is using every time you load your Newsfeed and accompanying ticker and chat windows, what exactly this data is, and how this data is stored and formatted. Here’s an example: (Scroll down for step-by-step instructions on … Read More