How does machine learning work? Myth and reality
There Are lots Of Myths about this Question that how does Machine Learning Works: I works automatically or It requires no modification and customization to by any third party to using it. Machine Learning can Solve any problem and fits into any business. What is truth behind it?
Machine Learning has great business potential Like any other technology but not always: It not Often the best solution to analyzing or process the unstructured information.
Machine Learning is a different way to execute command through computerized instructions, commands or Programs. Keep in mind that Machine learning is no Magic of miracle, Machine Learning is little to do with Human Intelligence.
Machine Learning is just a technology that learns through previous experience and training and processes of particular commands and inputs.
What characterizes machine learning techniques (and their limitations)
There Huge Machine Learning techniques, they all use the composed of co-occurrence and statistics. In simple language Machine learning doesn’t have a pre-build knowledge, It required the set instructions and documentations for training purpose (Larger set of documents, a better performance). The first essential training must be manual. Its requires a man works to perform first task.
Machine Learning can’t do everything Itself. In every scenario there is lot of man work is required.
The level of accuracy of a trained system will vary based on the number of documents used during the training phase and the coverage of the specific jargon in those documents. The system must also be retrained frequently to maintain the same level of quality.
Overloaded information will slow down the whore process and system too and over-fitting (too many documents of the same “genre”) can cause less accuracy. In simple words, The selection of wrong Documents can actually make the cause of decrease in quality.
From machine learning to Cognitive Artificial intelligence
Coming back to our question That “how does machine learning works?” we can say that machine learning easily supports the organization when we have a significant number of sample documents to train the ML algorithms and we have to face a simple scenario.
The analysis of project that is applicant of Machine learning is exactly a huge training set with unbiased distribution of all expected outputs.
Instead of when the scenarios that have a small and not uniformly distributed set of test samples and high complexity, Machine learning is not enough.
For these use cases, you need a linguistic engine that is sophisticated enough to ensure a deep understanding of the content and a set of tools that are powerful enough to ensure the development and effective application of advanced linguistic rules.