Machine learning recipes

Walk throughs and demonstrations of machine learning applications with code snippets and repo guidance.

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6 January 2017
5 min read
Sifting through lots of documents can be difficult and time consuming. Without an abstract or summary, it can take minutes just to figure out what the heck someone is talking about in a paper or report. And, if you need to get through hundreds of documents – good luck. Summarizer is an algorithm that...
30 December 2016
6 min read
In an earlier post, we introduced the Sentiment Analysis algorithm and showed how easy it was to retrieve the sentiment score from text content through an API call. In this post, we’ll show how to build a sentiment analysis pipeline that grabs all the links from a web page, extracts the text content...
22 December 2016
4 min read
Sentiment analysis is the process of identifying the underlying opinion or subjectivity of a given text. It generally categorizes these opinions on a scale from negative to positive. Some sentiment analysis algorithms include the neutral sentiment, too. These sentiments scores are generally used to...
16 December 2016
3 min read
Reading emotional expression is one of the most difficult tasks for humans, let alone computers. Two people looking at the same photo might not agree whether someone is grimacing or grinning. Until recently, computers weren’t much better at the job, either. Fortunately advances in deep learning has...
22 November 2016
7 min read
Last week we introduced the named entity recognition algorithm for extracting and categorizing unstructured text. In this post we’ll show you how to get data from Twitter, clean it with some regex, and then run it through named entity recognition. With the output we get from the algorithm,...
17 November 2016
5 min read
There’s been a lot of interest lately in a deep learning technique called style transfer, which is the process of reimagining one image in the style of another. It’s fun way to convert photos or images into the style of a masterpiece painting, drawing, etc. For instance, you could apply the...
12 November 2016
4 min read
Unstructured text content is rich with information, but it’s not always easy to find what’s relevant to you. With the enormous amount of data that comes from social media, email, blogs, news and academic articles, it becomes increasingly hard to extract, categorize, and learn from that information. While...
3 November 2016
3 min read
Let’s say you’ve created an awesome application that colorizes images. Everybody loves it, but some users are getting errors. You realize they’re trying to pass a URL to a webpage with an image on it, instead of a direct path to the image itself. Your app is expecting a .JPG, or...
28 October 2016
4 min read
Today, we’re excited to announce full development support for R on Algorithmia with our new CRAN package. R users now have access to Algorithmia’s library of more than 2,500 algorithmic microservices via the client. With the new client, R users can now deploy their predictive models and analytical...
27 October 2016
8 min read
Time series forecasting algorithms are a common method for predicting future values based on historical data using sequential data, such as snowfall per hour (anyone ready for snowboarding season?), customer sign-ups per day, or quarterly sales data. In this R recipe, we’ll show how to easily...