If you are building a mobile application of any sophistication, you are likely to need some services to support your app. You’ll need a way to distribute your app for testing prior to submitting to the app store(s), as well as analytics, error logging, crash reporting, and possibly user and data management services. Of course, you could write these services yourself and provision servers to host these services, but why do that when you don’t have to?
A spate of applications have popped/cropped up in recent years with slogans like “Make Anything Art.” They purport to transfer the style of one image and render the content of another image in that style. In the sets of images below, the small inset image is the source of the “style” which is transferred to the larger image. It’s an impressive trick, although I don’t know that it accurately represents what we mean by ‘style’.
I’ve partnered with my client, Texture, for more than two years, and I am still continually learning in all aspects of design. I’ve been lucky enough to pick up two software programs in the last year; Sketch and Principle. I’d like to give a quick review of Principle and share my pros and cons as a new user
3D printing is the process of creating a three-dimensional object by adding many layers of material together. This process is performed by a computer controlled machine commonly called a 3D printer. This article will primarily be discussing the Fused Deposition Modeling(FDM) method of 3D printing. Most FDM printers will heat up plastic and push it out from a nozzle. This process is called extruding.
Data visualization projects are probably what first drew me to software. I loved the idea of creating tools with beautiful interfaces that allowed people to see, interact, and play with big systems and concepts that are ordinarily hidden from view. Our lives are shaped and shaken by complex forces; making them tangible is a potent challenge, and one that really speaks to me.
In this post, I’d like to talk about some of the ways data visualization holds utility as a means of democratizing systems thinking, some considerations for how this can be effectively achieved, and how we might think of data visualization as a tool in our kit when approaching Big Serious Complex Problems.
Open Source software is ubiquitous today as a popular way to distribute software freely within the community. However, software licensing that is built on top of intellectual property laws is easy to overlook. Github shows that the percentage of their licensed public repositories has never passed 25% since 2009. Understanding these licenses and making the correct decision for a program can transform them into tools that can help creators’ intentions and goals for a project.
Kotlin is a JVM language that hit version 1.0 about a year ago (February 2016).
It is developed by JetBrains, the same people who make my favorite suite of
IDEs. The language itself is open-source under the Apache License 2.0 and is
developed as a community project over at kotlinlang.org. Kotlin is something
that I have become rather excited about over the past year. This post’s goal is
not to teach you Kotlin but to get you excited about it!
Machine learning (a field of artificial intelligence) is a rapidly expanding technology that we see in use more and more in our daily lives. It is used to give us more accurate results when we do an internet search, suggest products to us when we are shopping, and offer diagnoses to our maladies.
When developing websites it is important to consider your audience and how they interact with your application. This can be even more significant for a person with disabilities. Even the most stunning visual presentation can lose its value when the content cannot be interpreted by an individual due to, for example, a learning disability or difficulty seeing. Therefore, it is important, when doing any development or design, we do not dismiss the 1 in 5 people that would benefit on an accessible web.
Data mining is an interdisciplinary subfield of computer science used to discover patterns in complex datasets. The field has been widely studied since the 70’s since it can produce useful insights that can help to better understand underlying relationships and trends in data sets.