In a previous tutorial series I went over some of the theory behind Recurrent Neural Networks (RNNs) and the implementation of a simple RNN from scratch. That’s a useful exercise, but in practice we use libraries like Tensorflow with high-level primitives for dealing with RNNs.
Lagrange Points
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Creating a Search Engine
The science behind finding a needle in a needlestack.
How to scrape a website using Python + Scrapy in 5 simple steps
In this Python Scrapy tutorial, you will learn how to write a simple webscraper in Python using the Scrapy framework. The Data Blogger website will be used as an example in this article.
Grokking Deep Learning
If you passed high school math and can hack around in Python, I want to teach you Deep Learning.
Preliminary Note on the Complexity of a Neural Network
This post is a preliminary note on the “complexity” of neural networks. It’s a topic that has not gotten much attention in the literature, yet is of central importance to our general understanding of neural networks. In this post I discuss complexity and generalization in broad terms, and make the argument that network structure (including parameter counts), the training methodology, and the regularizers used, though each different in concept, all contribute to this notion of neural network “complexity”.
Evolution of active categorical image classification via saccadic eye movement
I put together a couple demo videos for our Active Categorical Classifier (ACC) project that we’ll be presenting at the PPSN 2016 conference.
Recurrent Neural Networks for Beginners
What are Recurrent Neural Networks and how can you use them?
Podcast Episodes 0 to 3
It’s been brought to my attention that iTunes only shows the last 10 episodes of the Becoming a Data Scientist Podcast. If you haven’t seen/heard episodes 0-3, you can watch the interviews on the YouTube channel:
Assorted links
