New in Big Data: Apache HiveMall - Machine Learning with SQL
It is widely accepted that applying Machine Learning techniques to data is a complex task that requires knowledge of a variety of programming languages and means hours of coding, compiling and debugging.
Not any longer!
Apache HiveMall is a Machine Learning library that allows anyone with basic knowledge of SQL to run Machine Learning algorithms.
- No coding
- No compiling
- No debugging
Apache HiveMall algorithms are hidden behind Hive UDFs. This allows end user to use SQL and only SQL to apply Machine Learning algorithms to a very large volume of training data.
Apache HiveMall Machine Learning Library makes training, testing, and model evaluation easy and accessible to a much wider community of business experts than ever before.
- Anyone who is interested in Machine Learning
- Why SQL?
- HiveMall Userguide
- Choosing environment
- Task Introduction
- Hands-on Example
Elena works in the field of Natural Language Processing. She graduated with a degree from Saint-Petersburg State University in Russia first and then acquired PhD from Macquarie University in Sydney, Australia, where she works currently. Now she applies theoretical concepts developed in the field of Natural Language Processing to solve business problems of different big and small enterprises.
As an early adopter of BigData tools and concepts she finds existing BigData frameworks to be attractive means of working with data. She started using such tools and advising other people to adopt BigData concepts way before Hadoop, Spark and other related technologies became “must to know” tools for many IT professionals.
Sharing knowledge is something Elena enjoys doing. She believes that sharing knowledge enriches her as much as other people.