All posts in Newsletter

September 2016 Newsletter: Need Some AI? Yeah, There’s a Marketplace for That

We’re excited to share that WIRED featured Algorithmia in an article earlier this month that looked at our efforts to democratize access to AI.

📝 From the Blog
This month we show you how to build a Slack chatbot to analyze the sentiment of a channel, create a tool that finds broken links, learn how to solve FizzBuzz using machine learning, and the easiest way to crawl and scrape every page from a domain. Read More…

Announcing Cloud Hosted Deep Learning Models with Support for GPUs (July 2016 Newsletter)

At Algorithmia, we believe in democratizing access to state-of-the-art algorithmic intelligence.

That’s why we’re introducing a solution for hosting and distributing trained deep learning models on Algorithmia using GPUs in the cloud.

Today, researchers and developers can train their neural nets locally, and deploy them to Algorithmia’s scalable, cloud infrastructure, where they become smart API endpoints for other developers to use.

We’re excited to announce initial native support for the Caffe, Theano, and TensorFlow frameworks, and have added 16 open source deep learning models that run as microservices to start. Support for Torch and MxNet are coming soon.

We’ve created two demos to showcase how easy it is to build applications from hosted models:

We want Algorithmia to be the place for researchers and developers creating deep learning models to showcase their work, distribute it, and make it available for other developers to use.

Let us know what you think.
– Diego M. Oppenheimer, Algorithmia founder and CEO


Turn Your Deep Learning Model into a Serverless Microservice

Hosting Deep Learning ModelsTrain your model using the tools you’re comfortable with. And, when you’re ready, deploy it to our infrastructure, where your model will join a collection of more than 2,200 algorithmic microservices other developers can use to obtain real-time predictions, and build production-ready, machine intelligent apps. Read more

Deep Learning Model Hosting Guides

Caffe | TensorFlow | Theano


16 Open Source Cloud Hosted Deep Learning Models Running as MicroservicesOpen Source Cloud Hosted Deep Learning Models

We’ve added 16 open source deep learning models to the platform for you to try today that use models from the TensorFlow, Theano and Caffe frameworks. Read more


Featured Deep Learning Models

Deep Face Recognition – A classifier that recognizes celebrity faces.

Nudity Detection Ensemble – Detect nudity in images with very high accuracy.

Parsey McParseface – Parse sentences with ease. Perfect for chatbots.


Don’t Know Where to Start?

Start here, or just reply to this email, and let us know what you’re looking for. We’d be happy to help.

  1. Getting Started Guide
  2. Developer Center
  3. API Documentation

Three Machine Learning and Artificial Intelligence Trends (June 2016 Newsletter)

This month, look at the three big machine learning trends and the future of artificial intelligence. 

We also learn how to turn a machine learning model into scalable, severless API, and how to setup an image processing pipeline to smartly crops photos. Plus, we feature the best new algorithmic microservices.

Have a question? Let us know @Algorithmia.


Three Machine Learning and Artificial Intelligence TrendsThe Future of AI and Machine Learning 2016

Every company is now a data company, capable of using machine learning in the cloud to deploy intelligent apps at scale, thanks to three machine learning trends: data flywheels, the algorithm economy, and cloud-hosted intelligence. Read more.


Turn Your Machine Learning Model Into a Scalable APIhosted-model-fb

Already have a trained scikit-learn or NLTK model? With Algorithmia you can quickly transform your model into a scalable, serverless microservice in just a few minutes. We’ll show you how with the guides below.

Plus, here’s an example of how we turned our GitHub README analyzer model into an API.

Model Hosting Guides:
scikit-learn | NLTK


Announcing Support for Amazon S3 and DropboxAlgorithmia Now Integrates with Amazon S3 and Dropbox

We’re excited to announce the Algorithmia Data Portal. A dedicated I/O hub that makes it easy to connect Algorithmia to Amazon S3 or Dropbox to access your data where it’s at.

Application developers can now read their data from an external source, process it using algorithmic microservices from Algorithmia, and then write the output where it’s needed. Read more.

Algorithmia Data Portal Guides:
Hosted Data | Amazon S3 | Dropbox


How To Create An Image Processing PipelineAmazon S3 Image Processing with Algorithmia

Need to create a simple image processing pipeline to batch edit photos? Here’s a quick way to automatically create thumbnails with custom dimensions using either Dropbox or Amazon S3.

In this demo, we’ll use SmartThumbnail, a microservice that uses face detection, to perfectly crop every photo to the same size without an awkwardly cropped heads or faces. Read more.


Featured Algorithms

Approximate Nearest Neighbors – A clustering algorithm that approximates the nearest neighbors.
Why You Need It: Find the approximate nearest neighbor from a dataset without sacrificing speed or memory.

File Converter – Convert files from one type to another.
Why You Need It: Always have your files in the format you need.

Reverse Geocoder  – Returns the city, country, and more from the latitude and longitude
Why You Need It: A fast, reverse geocoder that works offline.


Don’t Know Where to Start?

Start here, or just reply to this email, and let us know what you’re looking for. We’d be happy to help.

  1. Getting Started Guide
  2. Developer Center
  3. API Documentation

Thanks!
–Matt from Algorithmia