No fancy GPU processor? No time to leave your machine crunching for endless hours on a single machine learning task? Problems installing the endless dependencies your model requires? No problem.
Google Colab Notebooks are Jupyter Notebooks that run in the browser, using $10/month cloud GPU infrastructure from Google. This article will show you why and how to use them, implementing a style transfer example.
Training a style transfer model with satisfactory results might typically cost between $15-$20 on cloud GPU architecture for a single training job. …
This tutorial covers how to set up DeepLab within TensorFlow to train your own machine learning model, with a focus on separating humans from the background of a photograph in order to perform background replacement—also known as image segmentation.
I recently had what seemed like a very simple request on a project — given a gallery of projects, place a semi-transparent black overlay above any project the user had visited.
This article shows how to log contact form data that a user submits through your website into a Google Spreadsheet.
While a Google Spreadsheet is not the place most people would recommend you store important data — it can be a handy way for a lean organization to avoid dealing with databases, CMS, CRMs, etc…
TLDR: OpenCV’s camera doesn’t handle a mobile device’s portrait mode well by default. Grab the code below and drop it into
CameraBridgeViewBase to utilize the OpenCV rear and front facing Camera in full screen portrait orientation.
TLDR: Download the course material for: Visual Machine Learning, Machine Learning in Writing and Speech, and Machine Learning in Audio/Music.
I recently taught a series of workshops on Machine Learning at Pacific Northwest College of the Art’s Make+Think+Code program, and thought I’d make my course materials available online, with 3 goals in mind:
This is part 1 of my art focused Machine Learning Course. Click here to access the overview, which provides links to the other workshops in the series.
In this class we will be looking at Machine Learning as it relates to visuals: images, videos, etc. We’ll examine a few practical applications:
Utilizing a value-based system to interpolate…
This is part 2 of my art focused Machine Learning Course. Click here to access the overview, which provides links to the other workshops in the series.
Machine learning models within the context of language can operate quite differently than those used in Image Processing and other applications. For starters, because language follows such specific rules, when processing series of words, our ML models need to have some concept of what has come before them, what comes after them, and in what sort of context they are operating. …
This is part 3 of my art focused Machine Learning Course. Click here to access the overview, which provides links to the other workshops in the series.
In this class we’ll look at Machine Learning as it relates to Sound and Music. Many of the principles you learned in the previous classes will apply here, but manifest themselves in different ways.
We’ll look at a few concrete examples:
Using ML5, we’ll examine a user’s voice through the computer microphone and try to correctly identify musical notes. We’ll look at an example that makes a game of it, trying…
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