Millennials have a Problem with the NHS – Can AI Solve it? According to a survey by Prophet, the National Health Service is the “most relevant brand for UK consumers” at the moment. Edging out Apple and Spotify, the NHS’s relevancy is at #1, communicating positivity, recognition, and a general deep sense of importance.
According to a survey by Prophet, the National Health Service is the “most relevant brand for UK consumers” at the moment. Edging out Apple and Spotify, the NHS’s relevancy is at #1, communicating positivity, recognition, and a general deep sense of importance.
Yet not everyone shares this sentiment wholeheartedly. Amongst the surveyed, British millennials have shown less appreciation for the NHS, compared to older generations. This is hardly surprising. For the past few years, reports have been signifying the disconnection between the NHS and the millennial demographic, both as patients and the soon-to-be biggest part of the workforce in the service.
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.
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7 Types of Data Bias in Machine Learning. Data bias can occur in a range of areas, from human reporting and selection bias to algorithmic and interpretation bias.
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
In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics.