Machine Learning and Data Science: An Overview
Information and technology have made data the driving force behind contemporary day
innovation and progress. An enormous amount of data is produced by our daily activities,
conversations, and technological usage. The fields of Data Science and Machine Learning, which are
closely related, have emerged as potent resources for mining this data for insights. In
this introductory article, we'll go into the basics of Data Science and Machine Learning, covering
their core ideas and explaining why they're so important in today's data-driven society.
Science of Collecting and Analyzing Data to Draw Conclusions
Data science is the study of how to gain useful information from large datasets. It's
a multidisciplinary field that uses statistics, programming, domain knowledge, and data
visualization to tackle tough issues. Data science is fundamentally concerned with the
transformation of raw data into useful insights.
There are a few main stages in the Data Science process:
Data collection is the process of amassing information from numerous sources, such as
databases, written documents, and social media platforms or application programming interfaces
(APIs). For any data science endeavor to be fruitful, both the quality and quantity of the data at
hand are required.
