Liberating PDF Data: Introducing Our Newest API

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PDF, or Portable Document Format, files were developed to enable people using different operating systems to open, review, and print files without altering any of the file’s original elements or design. Successful adoption of this format over the years means that there is now a wealth of information stored in PDF files. Extracting that information… Read more

Building a Bot for Better Customer Support

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In a startup, we wear many hats. Operations does a little bit of sales, marketing does a little bit of quality assurance, engineering contributes to the blog…and everyone takes pride in helping out with customer service. For many months, we had one person managing questions we received through our little Intercom chat window (you know,… Read more

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

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In knowledge driven economies, it’s increasingly common for many jobs to revolve around the consumption and analysis of information. This may entail, for example, reading dozens of articles to draw conclusions about emerging trends. Doable, right? Imagine, though, if you were a financial analyst and had to read through hundreds of articles and reports each… Read more

Build Customized Deep Learning Models, No Code Required

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General, pre-trained machine learning solutions are now easier to come by — sentiment analysis, topic classification, entity extraction, etc. Unfortunately, these solutions typically don’t work so well with industry or company-specific tasks, because the data that matters for your business is probably different from the data used to train the model. For instance, financial articles… Read more

SAS: The Unreasonable Benefits of Deep Learning

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Earlier this month, Dan gave a talk at Sentiment Analysis Symposium discussing why businesses should consider adopting deep learning solutions. His slides and a video of the presentation are available for those of you who couldn’t make it — if you have any questions, click the little chat bubble at the bottom right hand corner… Read more

Semi-supervised Feature Transfer: The Practical Benefit of Deep Learning Today?

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In this case study, we evaluate four different strategies for solving a problem with machine learning. In terms of both technical performance and practical factors like economics and amount of training data required, customized models built from semi-supervised “deep” features using transfer learning outperform models built from scratch, and rival state-of-the-art methods. Featured on KDnuggets.… Read more