Last Updated on by Kumar Raja

How Machine Learning Has Revolutionized Data Science?

We are very well aware of the fact that being an interdisciplinary field, Data Science makes use of concepts in Mathematics, Programming, Computer Science, AI, Machine Learning & several other domains to be able to accurately interpret with Big Data. Every field has its own impact on Data Science. Machine Learning, a subset of Artificial Intelligence which is a recent addition into Data Science is proving out to be a great asset that is empowering Data Science at large. With the help of Machine Learning, we can automatically and quickly apply mathematical calculations to big data & achieve the desired results.

The addition of Machine Leaning into Data Science is creating many wonders in the field of Big Data analysis. A Data Scientist must surely be having knowledge of how Machine Learning algorithms function so that they would be able to apply the right algorithm on the relevant data problem to obtain the accurate results. With the growing prominence of Machine Learning in the field of Data Science, many companies are showing interest to recruit Data Scientists who have intense knowledge of Machine Learning.

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Impact of Machine Learning In Data Science:

Machine Learning is an advanced technology in the field of Artificial intelligence. It has a number of algorithms that could help the Data Scientists in analyzing large chunks of data. It takes down a lot of effort from the shoulders of Data Scientists by automating the data analysis process & it is for this reason that it has gained a lot of prominence and recognition.

With the integration of Machine Learning in Data Science, a lot of changes have taken place in the way data is extracted and interpreted. Machine Learning has also replaced the traditional statistical techniques. Also, by training the data models with Machine Learning algorithms, Data Scientists can make accurate predictions that would help them to make accurate decisions.

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