Goodreads is one of my favorite services, as I love reading (and spend quite a bit of time doing it, to be honest). My goal for 2019 is to read 75 books, and an additional 3 books in German as I’ve been learning the language over the last couple of years. Here’s where I’m at so far, and we’re only in January:
The ImageDataGenerator class in Keras is a really valuable tool. I’ve recently written about using it for training/validation splitting of images, and it’s also helpful for data augmentation by applying random permutations to your image dataset in an effort to reduce overfitting and improve the generalized performance of your models.
Keras comes bundled with many helpful utility functions and classes to accomplish all kinds of common tasks in your machine learning pipelines. One commonly used class is the ImageDataGenerator. Until recently though, you were on your own to put together your training and validation datasets, for instance by creating two separate folder structures for your images to be used in conjunction with the flow_from_directory function.
make is a widely used and powerful took for coordinating common tasks within a project, and you'll often file a **Makefile** sitting in the root of open source repositories, allowing you to quickly see how to perform common tasks such as running tests, compiling and running, etc. But many developers don't realize you can also run make targets in parallel to accomplish some impressive feats.
The goal of this post is to train a convolutional neural network to properly play Conway’s Game of Life without explicitly teaching it the rules of the game.
I thoroughly enjoy writing and generally when I write, I do so using Markdown for formatting. Markdown is great because it can be easily exported to HTML, a PDF, Word Documents, etc. There's great tooling around Markdown, abd it's a well supported markup language. My only problem is when I'm writing larger documents, such as if you were to write book, you quickly end up with a massive, unwieldly document. That's where modoc comes in!
TensorFlow is a modern machine learning framework that provides tremendous power and opportunity to developers and data scientists. One of those opportunities is to use the concept of Transfer Learning to reduce training time and complexity by repurposing a pre-trained model.
In Parts 1 and 2 of the OpenGL with Go Tutorial we learned how to draw shapes and created a grid that will act as our game board. Now it's time to implement Conway's Game of Life and see some simulations!
In Part 2 of the OpenGL with Go Tutorial we pick up with the triangle we left off with, and make a square out of two triangles. Then, we make an entire grid of squares to act as our game board.
OpenGL is pretty much the gold standard for any kind of graphics work, from desktop GUIs to games to mobile applications and even the web, I can almost guarantee you’ve viewed something rendered by OpenGL today. However, regardless of how popular and useful OpenGL is, it can be quite intimidating to get started compared to more high-level graphics libraries. The purpose of this tutorial is to give you a starting point and basic understanding of OpenGL, and how to utilize it with Go. There are bindings for OpenGL in just about every language and Go is no exception with the go-gl packages, a full suite of generated OpenGL bindings for various OpenGL versions.
