Interpreters, machine learning and low-level stuff — Reading List
Back to the online society. Work has been taking a lot of my time and energy, and I’ve begun to make a major effort to work on side projects that I can show off. In next few posts, I will talk about that.
Now, here’s a list of content that I find interesting enough that I saved it to my email:
Crafting interpreters — http://www.craftinginterpreters.com/
A book in progress on how to write a compiler. It’s not finished yet but already has some interesting chapters. It’s written by a Google Engineer that has a game development background.
Predictive superpowers: Applying deep learning on mobile sensor data to predict human behavior
This is a well put together analysis on how to predict human actions using an LSTM.
QuickNet: Maximizing Efficiency and Efficacy in Deep Architectures — https://arxiv.org/pdf/1701.02291.pdf
There’s been a major effort to optimize how fast Deep Neural Networks run on mobile devices. I’ve been interested in this topic, and this was one of the first links I found talking about this topic. I also like its informal style.
www.alanzucconi.com
Alan Zucconi has a pretty awesome blog. He writes about a variety of topics, from computer graphics to machine learning. All posts are interesting and really well illustrated.
Sentiment Analysis on Reddit News Headlines with Python’s Natural Language Toolkit (NLTK)
This post shows how to build a dataset and perform sentiment analysis using Reddit’s API.
Machine Learning with Small Data
A small blog post that talks about the implications of having to solve hard machine learning problems with low amounts of data.
Convolutions methods for text
How to use convolutions based neural networks instead of RNN’s.
Open Information Extraction in Portuguese
How to do Information Extraction in Portuguese News. A significantly harder problem than doing it in English given the available tools and data.
Eye shader breakdown
A shader breakdown of a fun visual.
How a 64k intro is made
What goes into a 64k demo entry? It’s really fun to see the tools and methods those guys and gals use to build a demo for a competition.
Writing a Really, Really Fast JSON Parser
A low-level breakdown on how to write a fast JSON parser.
That’s it. I really should turn this into a newsletter; I think it would fit the format.
In the next post, I’m pretty sure I will talk about a few side projects I’ve been working on so stay tuned for that!
