Difference between Machine Learning and Predictive Analytics
1. Machine Learning :
Machine learning is the subject of AI that makes use of statistics, fundamentals of computer science and arithmetic to construct good judgement for algorithms to operate the project such as prediction and classification.
2. Predictive Analytics :
It entails certain manipulations on statistics from current records units with the purpose of figuring out some new traits and patterns. These trends and patterns are then used to predict future results and trends. The sole purpose of this is to compute the value of a specific variable at a future factor of time. Predictive analytics is close information loaded whilst machine learning is more of a combination of statistics, programming, and mathematics.
Difference between Machine Learning and Predictive Analytics :
|It acts as an umbrella which covers different subfields including Predictive Analytics.
|It is a subset of Machine Learning.
|Computer Science is the root of Machine Learning.
|Its root is Statistics which plays important role in predictive analytics.
|It is in trend and latest technology as compared to Predictive Analytics.
|It is not used much as compared to Machine Learning.
|To process task, it requires a lot of coding and a high amount of data as compared to Predictive Analytics.
|To process task, it does not require a lot of coding compared to Machine Learning.
|Machine is responsible to take decision and process task without human intervention.
|Human intervention is required to process a particular task.
|For solving a problem, there are various tools and languages are available such as Python, SaaS, etc.
|To process task, there are various tools and languages are available such as Minitab, Excel, etc.
|Machine learning is very vast.
|It is not very vast and has a limited area to look into.
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