At Textron Systems, digital transformation is core to our strategy, not only from the attitude of how we execute our business but also how our products and services are differentiated. A key enabler to digital transformation is leveraging an ecosystem of ’as-a-service’ offerings that bring the required capabilities and operational performance to our solutions. Beyond the elasticity that these architectures provide, they also enable access to a marketplace of services like machine learning, advanced analytics, and proven algorithms. Machine learning represents a chance for commercial, civil and government organizations alike to drive powerful economies like cost reduction, productivity optimization, and merchandise differentiation. to realize these benefits, organizations must implement machine learning with an eye fixed toward avoiding their commonest failure modes.
First and foremost, data is vital when it involves machine learning. The more data you've got for the advanced algorithms to find out from, the upper the probability of driving desired and meaningful insights. There are inherent challenges to perfecting machine learning insights, starting with the cleanliness, or quality, and availability of excellent data sets to mine, or “learn” from. There are several applied examples where biases in data have skewed the results and accuracy of knowledge insights through machine learning concepts. Training an algorithm is like training a body; the healthier the inputs, the higher the probabilities of improved performance.