System does self-discovery of patterns, regularities and features etc. from the input data and relations for the input data over output data. Discovering similarities and dissimilarities to forms clusters i.e. self-discovery is main target here. Since the examples given to the learner are unlabeled
Machine learning algorithms “learns” from the observations. When exposed to more observations, the algorithm improves its predictive performance. What’s going to happen to the stock market tomorrow? Is a task of deducing function from labeled training data.
Machine learning is subset to Artificial Intelligence which borrows principles from computer science. It is not an AI though; It is focal point where business and experience meet emerging technology and decides to work together.
AI is Transforming the Digital Economy through FinTech. How its doing that we will answer below by taking help through “Cognitive Ergonomics”. May assuming AI more human then it is.
Machine learning is the process of a machine attempting to accomplish a task, independent of human intervention, more efficiently and more effectively with every passing attempt i.e learning phase. At this point, AI- a machine which mimics the human mind, is still a pipe dream. In the middle we have the meat of the pipeline, the model, which is the machine learning algorithm that learns to predict given input data.