In the evolving world, there exist a lot of confusions in the technological terms such as artificial intelligence, Data Science, machine learning, deep learning and so on. While they are closely interconnected with each other.
Over the past few years, the popularity of these technologies has risen to such an extent that several companies have now woken up to their importance on massive levels and are increasingly looking to implement them for their business growth.
This post will help you to get a clear picture about the difference between Machine Learning and Data Science.
Data Science
Data Science is a detailed study of the flow of information from the colossal amounts of data present in an organization’s repository. It involves obtaining meaningful insights from raw and unstructured data which is processed through analytical, programming, and business skills.
Importance of Data Science:
In a world that is increasingly becoming a digital space, organizations deal with zettabytes and yottabytes of structured and unstructured data every day. Evolving technologies have enabled cost savings and smarter storage spaces to store critical data. In here, Data Science plays a role where it extracts information from unstructured data.
Machine Learning
Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.
Importance of Machine learning
Data is the lifeblood of all business. Data-driven decisions increasingly make the difference between keeping up with competition or falling further behind. Machine learning can be the key to unlocking the value of corporate and customer data and enacting decisions that keep a company ahead of the competition.
Comparing Data Science and Machine learning
Machine learning is a component of data science; where data science as the larger picture comprises of big data, data learning, statistics and much more. Machine learning involves the use of programming and computational algorithms to arrive at a conclusion, whereas data science uses numbers and statistics to bring a result.
For companies that are more data-driven, switching to data science is a secret mantra for enhancing business and for targeting better returns on investments. Machine learning, on the other hand, in today’s date, is essential since it can solve intricate and complex computational problems by breaking them down into bits.
