Machine learning, data science, and data analytics or scientists are emerging fields growing into various sub-fields, helping companies improve their efficiency and performance at certain stages during the operations and services. Hence, understanding these technologies is very important to realize their right use and benefits into various sectors. So, here we have discussed what data science is and what is machine learning with few sets of examples.
What Is Data Science?
Data science is a term used for dealing with big data that includes data collection, cleansing, preparation, and analysis for various purposes. A data scientist collects data from multiple sources and after analysis, applies into predictive analysis or machine learning and sentiment analysis to extract the critical information from the data sets. These data scientists analyze and understand the data from a business perspective and give useful insights and accurate predictions that can be used while taking critical business decisions.
What is Machine Learning?
Machine Learning is defined as a practice of using the suitable algorithms to utilize the data for learning and predict the future trend for a particular area. Machine learning software contains the statistical and predictive analysis that is used to recognize the patterns and find the hidden insights based on perceived data. The best examples of a machine learning application are Virtual assistant devices like Amazon’s Aleza, Google Assistance, Apple’s Siri, and Microsoft’s Cortana. Social platforms like Facebook work on machine learning principles and predict or respond as per the past behavior of the users to suggest them the most suitable things.
Both data science and machine learning as a service have their own uses and are important to various fields, but both are based on data that can be gathered, analyzed, and applied into predicting certain answers in a specific field. Data science is simply related to data gathering and analysis, while machine learning datasets are the process of feeding datasets for training the machines with the help of certain algorithms as per the requirements. The main difference between data science and machine learning is that data science covers the whole spectrum of data processing, not just the algorithmic or statistical aspects.