Common Misconceptions about Machine Learning

Maself-learn and improve from the past data inputs and predict the future output on the basis of statistical analysis without being explicitly programmed. With the application of artificial intelligence, machine learningused to take place behind the scene web activity prediction and has now found new grounds in the field of marketing, technology (self-driving cars) and effective web searches. Along with this growing application, several machine learning misconceptions have grown about it with false expectations leading to failure for data scientists.

Common Misconceptions about Machine Learning are mentioned below

Large data leads to a more accurate outcome

We expect that more the data is fed to Machine learning algorithm the more accurate and intelligent it gets and make decisions like a human. But, there is a trick named transfer learning where you can teach a machine learning system to use a large data set and transfer it to a small amount of data and get better outcomes.

Machine Learning = Artificial Intelligence

Machine learning and AI are often used together or interchangeably but both are very different from each other Machine learning is more about predicting the outcome on the basis of previous statistics. While artificial intelligence is a much wider area having robotics, computers and smart devices able to perform tasks requiring human intelligence.

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