Autonomous aircrafts exist today, and we’re not simply referring to drones. Over recent years, automated artificial intelligence (AI) flight systems have taken on more and more tasks from pilots
Autonomous aircrafts exist today, and we’re not simply referring to drones. Over recent years, automated artificial intelligence (AI) flight systems have taken on more and more tasks from pilots. Today, these systems have taken on the role of an additional (not replacement) co-pilot. The benefit goals? Flight crews will have less stress and a reduced risk of pilot error. In an industry that is projected to have a shortage of pilots, AI solutions may be the solution that will prevent your next flight cancellation. And why not? Machine vision is currently used in cars, and there should be no reason why these applications can’t be scaled with precision and caution for aircrafts. AI has the potential for great logistics tools, including fleet management. Airlines can expect two significant results from implementing AI logistic capabilities:
This "Deep Learning vs Machine Learning vs AI vs Data Science" video talks about the differences and relationship between Artificial Intelligence, Machine Learning, Deep Learning, and Data Science.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
A couple of days ago I started thinking if I had to start learning machine learning and data science all over again where would I start?
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Artificial Intelligence (AI) vs Machine Learning vs Deep Learning vs Data Science: Artificial intelligence is a field where set of techniques are used to make computers as smart as humans. Machine learning is a sub domain of artificial intelligence where set of statistical and neural network based algorithms are used for training a computer in doing a smart task. Deep learning is all about neural networks. Deep learning is considered to be a sub field of machine learning. Pytorch and Tensorflow are two popular frameworks that can be used in doing deep learning.