Python 3.7: Gains that Eliminate Pains20180802214501

Python 3.7: Gains that Eliminate Pains

Pete GarcinAugust 2, 2018,
In development for 10 months, Python 3.7 has just been released. For long time Python users, it’s a welcome addition, providing many quality of life e...
Machine Learning – The New Cornerstone of Digital Transformation20180502172132

Machine Learning – The New Cornerstone of Digital Transformation

Artificial Intelligence (AI), and more pragmatically, Machine Learning (ML) have been called the new electricity that’s powering the Fourth Indu...
Options for Deploying Machine Learning Algorithms to AWS20180117190038

Options for Deploying Machine Learning Algorithms to AWS

Christopher ShoeJanuary 17, 2018, , , , , ,
AWS is a great place for accessing scalable, cheap resources on which to deploy data models. However, actually using AWS for this purpose can be chall...
Poodle, Pug or Weiner Dog? Deploying a Dog Identification TensorFlow Model Using Python and Flask20180110210017

Poodle, Pug or Weiner Dog? Deploying a Dog Identification TensorFlow Model Using Python and Flask

Pete GarcinJanuary 10, 2018, , ,
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 sim...
How to Deploy Machine Learning Models to a .NET Environment20180103150000

How to Deploy Machine Learning Models to a .NET Environment

Christopher ShoeJanuary 3, 2018, , , , ,
Python and R are among the most popular programming languages for data-centric engineers. However, they are not always the languages that the rest of ...
Optimizing Machine Learning with TensorFlow20171122140120

Optimizing Machine Learning with TensorFlow

Pete GarcinNovember 22, 2017, , , ,
In our webinar “Optimizing Machine Learning with TensorFlow” we gave an overview of some of the impressive optimizations Intel has made to TensorFlow ...
Python vs C++ for Text Processing20171115140311

Python vs C++ for Text Processing

Tom RadcliffeNovember 15, 2017, , , , , ,
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 com...
Accelerating Your Algorithms: Considerations in Design, Algorithm Choice and Implementation20171102130109

Accelerating Your Algorithms: Considerations in Design, Algorithm Choice and Implementation

Tom RadcliffeNovember 2, 2017, , , ,
The pursuit of speed is one of the few constants in computing, and it is driven by two things: ever-increasing amounts of data, and limited hardware r...
Robust Algorithms for Machine Learning20170720141501

Robust Algorithms for Machine Learning

Machine learning is often held out as a magical solution to hard problems that will absolve us mere humans from ever having to actually learn anything...
Machine Learning, Intel MKL and Shooting Space Aliens at PyCon 201720170602160007

Machine Learning, Intel MKL and Shooting Space Aliens at PyCon 2017

One of the best parts of PyCon 2017 was meeting with the amazing folks from the Python community. We had a great three days at the conference and the ...
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