Understanding the Difference

Data science, data analytics, and machine learning are terms that are often used interchangeably when talking about making sense of big data. But this is wrong. Data science is a field that studies data and how to extract meaning from it, whereas machine learning is a field devoted to understanding and building methods that utilize data to improve performance or inform predictions. Machine learning is a branch of artificial intelligence (AI). CDO Trends brought this interesting topic to us in their article, “Deciphering Data Science and Machine Learning.”

Data science encompasses a rich variety of techniques and methods. For instance, extracting insights and knowledge from data often necessitate tasks such as data cleaning, exploration, and visualization, while the application of statistical and machine learning models are required to make predictions or identify patterns.

Data science today is an integral part of many industries. Working with data helps companies to better understand their customers, optimize business processes and offer better products.

Data Harmony is a fully customizable suite of software products designed to maximize precise and efficient information management and retrieval. Our suite includes tools for taxonomy and thesaurus construction, machine aided indexing, database management, information retrieval, and explainable AI.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.