indico Blog

Resources for exploring machine learning and data science

December 12, 2016

Posted by
indico

Liberating PDF Data: Introducing Our Newest API

It's relatively easy to collect and use online data for analysis and training machine learning models. There's also a wealth of information stored in offline documents, like PDFs, but the limitations of existing tools make it difficult to access that data efficiently -- so we developed an API to address this.

November 28, 2016

Posted by
Amanda Sivaraj

Building a Bot for Better Customer Support

With a little bit of nifty machine learning, we built a bot to manage customer enquiries more efficiently and improve the timeliness of our responses. In this tutorial, we’ll show you how to train your own IntercomBot using our customizable machine learning API, Custom Collections.

November 15, 2016

Posted by
Madison May

Data Science Deployments with Docker

Deploying machine learning models has always been a struggle. With the recent release of NVIDIA's nvidia-docker tool, however, accessing GPUs from within Docker is a breeze, and we're already reaping the benefits here at indico. In this tutorial, we’ll show you how to set nvidia-docker up so you can also deploy machine learning models with ease.

November 3, 2016

Posted by
indico

Read Less, Learn More: Introducing indico’s Summarization API

When faced with information overload, let machine learning come to the rescue. The new indico Summarization API is designed to read through an article and pick out key, “big idea” sentences so you can quickly determine whether the article’s content will be useful to you.

October 18, 2016

Posted by
Amanda Sivaraj

Build Customized Deep Learning Models, No Code Required

Introducing CrowdLabel, the latest addition to our machine learning toolkit. CrowdLabel provides a quick and seamless way to build custom models around your data -- all without writing any code. Use it to create a customized topic tagging model in this tutorial.

October 4, 2016

Posted by
indico

TensorFlow in Practice (Video + Slides)

TensorFlow is a wonderful tool for rapidly implementing neural networks. Nathan Lintz teaches the basics of TensorFlow and how to build neural networks in just a few lines of code at the Boston Machine Learning Meetup.

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Recent Posts

Exploiting Text Embeddings for Industry Contexts

From Synonyms to Object Properties It’s well known that word embeddings are excellent for finding similarities between words --... more

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Making Deep Learning Practical with Smaller Datasets

At the recent VB Summit in Berkeley, Jeff Dean, Head of Google Brain discussed a popular challenge in making Deep Learning a practical... more

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Building Better Search

In speech and writing, how often do we use one term -- and only that term -- to describe an idea? For example, if you were searching... more

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