ActiveState Blog

In my last post I surveyed the growing array of options for deploying your ML models into production. In this post, we’ll create a demo to see how simple it is to develop your own service using Python’s Flask library.

There are a number of cases where you might not be able to use a cloud service to host your model and would be required to roll-your-own inference service. In many large enterprises, on-premise solutions are mandatory. Approvals to purchase third-party solutions can also be lengthy and complex. So developing your own small service may be the best solution.

Hadoop is an open-source software framework for distributed storage and distributed processing of very large data sets. All the modules in Hadoop are designed with an assumption that hardware failures should be automatically handled by the framework.

We’re heading towards the end of year and I’m reflecting on what I’ve accomplished in 2017. A big part of my 2017 effort was on the recent release of Komodo 11. That got me thinking about my favourite features in Komodo 11. I’m still excited about them and have been using them a lot since the 11.0 release. I think users will love them too.

The features are (listed in alphabetical order, I couldn’t like one more than the other!):

Machine Learning (ML) powers an increasing number of the applications and services that we use daily. For organizations who are beginning to leverage datasets to generate business insights -- the next step after you’ve developed and trained your model is deploying the model to use in a production scenario. That could mean integration directly within an application or website, or it may mean making the model available as a service.

Text will always be a major format for data and it will never be well-organized. According to Phil Karlton’s famous joke, the two hard problems in computing are naming things, cache invalidation, and off-by-one errors. A third problem could be “formatting things”. Most textual data has irregularities in the formatting that make it a pain to process. And much of the work in text processing goes into dealing with formatting issues. These are just the sad facts.