All posts in Algorithm Spotlight

Rapidly Extract Information from Public Websites

We have a lot of fun, heavy-hitting algorithms in our marketplace: deep-learning tools like Image Tagger and pipelining mechanisms such as Video Metadata Extraction are designed to bring the power of Machine Learning to your app via easy-to-use APIs.

But sometimes, all you need to do is extract some simple information from publicly available sources: for example, finding all the email addresses of a company’s C-Suite, or summarizing the topic pages of a FAQ. You could accomplish some of it with a Python script and some RegEx magic, but that wouldn’t bring the benefits of a remote API: datacenter-grade network connections, multiple IPs, and distributed parallel processing. And it wouldn’t give you access to more complex algos such as automatic tagging or sentiment analysis. With Algorithmia, you get all the benefits of the cloud without having to build and host your own workers, plus the combined experience of our growing network of experienced algorithm developers. Read More…

Train a Machine to Turn Documents into Keywords, via Document Classification


Figuring out the meaning of a document was once a very hard problem for computers to solve… even for humans, understanding the complexity of natural language can be tricky!

Fortunately, there are some great tools that can help address those concerns. The Document Classifier turns your existing documents and associated keywords into a model which can be used to predict the most appropriate keywords for new blocks of text. Read More…

Introduction to Video Tag Sequencing

Video Metadata Extraction

Sifting through unlabelled videos can be difficult and time-consuming. Even for the most seasoned analyst, fatigue leads to mistakes. Whether you’re trying to detect anomalies in mission-critical infrastructure — or you just want to find all of the segments in your vacation videos that contain ducks — we have a microservice that can help reduce the workload.

What is the Video Tag Sequencer? How does it work?

The VideoTagSequencer is an algorithm takes the time series point data generated from VideoMetadataExtraction and converts it into an index of detected labels and sequences contained in the video. In a nutshell, it takes frame-by-frame results, and converts them into a list of time ranges at which each result occurs. Read More…

Style Transfer with StyleThief

Style transfer is a term used for reimagining an image with the style of a given piece of art. Recently, various research groups have proposed different approaches to do style transfer. Generally speaking, there are trade-offs between these different techniques.

For example, in one of our previous spotlights we talked about DeepFilter, where you train a model based on a style, and stylize images almost instantaneously with that trained model. You would train for about a day, and later be able to stylize images rapidly. The biggest issue with this technique is that training wouldn’t always yield the best results. You would then need to train it multiple times, which could easily add up to a few days.

StyleThief works differently from DeepFilter. It takes a long time to train for every sample image, but is more robust and yields better stylized images. It is a trade-off between speed and quality. Read More…