Optimizing Your Solutions with K-Means Clustering
No matter how much we know, the key point is the ability to deliver an artificial intelligence (AI) solution. Implementing a machine learning (ML) or deep learning (DL) program remains difficult and will become more complex as technology progresses at exponential rates.
There is no such thing as a simple or easy way to design AI systems. A system is either efficient or not, beyond being either easy or not. Either the designed AI solution provides real-life practical uses, or it builds up into a program that fails to work in various environments beyond the scope of its training sets.
This chapter doesn't deal with how to build the most difficult system possible to show off our knowledge and experience. It faces the hard truth of real-life delivery and ways to overcome obstacles. For example, without the right datasets, your project will never take off. Even an unsupervised ML program requires reliable data in...
