The top 3 reasons why Machine Learning models are so important is as given below:
- Machine Learning models can “uncover difficult-to-analyze relationships”
Deep neural networks and other machine learning algorithms are particularly adept at spotting difficult-to-analyze patterns in massive data sets. For example, machine learning models are able to identify thousands of photos and video frames per second, transcribe the audio in real-time, and search for malignant patterns in x-ray and MRI scans.
2. Machine Learning models can “capture various nonlinearities”
In statistics, the word “nonlinearity” is used to describe a scenario in which an independent variable and a dependent variable do not have a straight-line or direct relationship. Changes in the output are not directly proportional to changes in any of the inputs in a nonlinear connection.
Machine-learning algorithms can detect significant nonlinearities in the data.
3. Machine Learning models can “process unstructured data”
Unstructured data is any data that does not adhere to a data model and has no obvious organization, making it difficult for computer programs to use. Unstructured data is not well suited for a common relational database since it is not organized in a predefined way or does not have a predefined data model. For example web page data, Image data, Videos data.
Machine Learning models can process unstructured data
Please let me know in the comments if you find more reasons for “Why is the Machine Learning model so important?”
Happy Learning :)
