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 learning used 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.

Data you have is useful

The machine learning model you create will apply only specific patterns and look out for them in the data you feed in. Only the relevant data should be feed to the program as the rest of the data will not Only well-labelled data that will match the queries you are going to request needs to be asked. Thus we can interpret that ML needs data but not all the data you have.

Unbias

As we know that ML works on the input dataIt’s important to remove the bias in the data set input to avoid any unrelated item recommendations.

ML will one day replace human

According to the current phase of increasing automation, With improved efficiency, reduced costs and but in the long run the results will be different than what's predicted ML will create new jobs and business opportunity. With implementation in business process and marketing, ML has drastically improved offering improved customer experience with predictive analysis and helping decision makers like never before.