TOP 5 AUTOML TOOLS EASING OUT MACHINE LEARNING FOR NON-EXPERTS Posted on : Nov 22 - 2019

The boons of machine learning have been leveraged in the industry in the past many years. With its increasing implementation, the ML tools have also evolved with time. Today, people can easily work with machine learning owing to its easy-to-use, user-friendly tools. As the gathering of data and turning it into actionable insights has been automated enough, people with some knowledge of technology and motivation can work with ML.

These tools possess the strength to handle the mundane work of collecting data, adding structure and consistency where possible, and then starting the calculation. The modern-day tools can simplify the data gathering process and keeping that information in rows and columns.

Such user-friendly features are paving the way for people who work with numbers, spreadsheets and data towards machine learning while eliminating the need to be great at programming and data science.

Below are the five tools that simplify using machine learning algorithms.

Splunk

Splunk’s original version started off as a tool for searching through the voluminous log files created by modern web applications. Since then it has grown to analyze all forms of data, especially time-series and others produced in sequence. The latest newest versions of Splunk includes apps that integrate the data sources with machine learning tools like TensorFlow and some of the best Python open-source tools. Such modern tools offer quick solutions for detecting outliers, flagging anomalies and generating predictions for future values.

DataRobot

DataRobot incorporates a variety of regression techniques, ranging from the simplest (linear regression) to complicated statistical classic regression models, to more complex techniques including gradient boosting and neural networks. View More