Machine Learning

 

 

HPCC Systems Git support

Gavin Halliday is a longstanding member of the HPCC Systems core development team. In this blog Gavin outlines the new improvements added to GitHub and discusses the best way to implement them. Learn how to use these improvements to have the most optimized experience possible.

Academic Spotlight: Performance Skew Prediction in HPCC Systems

HPCC Systems has a robust Academic Program that collaborates with colleges, universities, high schools and institutions of higher learning around the world. One such collaboration with the Rashtreeya Vidyalaya College of Engineering (RVCE) in Bengaluru, India, has resulted in a new publication: Performance Skew Prediction in HPCC Systems, published by IEEE Xplore®

 

Advanced Python Embedding in ECL — A definitive guide

ECL Provides a powerful capability to combine the benefits of declarative programming (ECL) with those of procedural languages such as C++, Java, or Python. This is known as Embedding. This guide provides a comprehensive review of various methods and patterns for Python Embedding within ECL programs. It reviews elementary embedding techniques, and provides a guide to several more advanced embedding patterns.

 

Academic Spotlight: VR Supermarket- a Virtual Reality Online Shopping Platform with a Dynamic Recommendation System

HPCC Systems has a robust Academic Program that collaborates with colleges, universities, high schools and institutions of higher learning around the world.

One such collaboration with the Rashtreeya Vidyalaya College of Engineering (RVCE) in Bengaluru, India, has resulted in a new publication:

 

The Hidden World of Unicode – From Text to Emojis

When we use our smart phones, we are used to texting each other using our own native language, often a second language (more and more people are multi-lingual), and something newer than text: emojis. Not only do smart phones have to deal with all this, servers, databases, text processors, and even machine learning have to be able to navigate this strange world of modern text. But how do they do it?

Random Fourier Features accelerated Gaussian Process Regressor

Gaussian process regression is a powerful machine learning method to solve non-linear regression problems. However, because of the intensive computation, Gaussian process regression is not suitable for large-scale machine learning problems. Fortunately, researchers developed approximation methods to get a solution arbitrarily close as the original Gaussian process more rapidly and with better scaling. In this post, a Random Fourier Features accelerated Gaussian process regressor will be introduced.

 

 

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