I think we can all agree that collaboration is a good thing and that our combined thinking is greater than the sum of its parts. Why, then, do we feel the need to take a different view when it comes to working with artificial intelligence?
In previous articles, we’ve discussed the importance of collaboration between the experts working in different fields of study. Real world problems don’t tend to fall neatly into the scope of one particular area of research — we need to learn to face problems together by not only sharing what we know, but also by being willing to listen — carefully — to the ideas of others. We need to remain open enough to admit that we don’t have all the answers and that someone else may have knowledge and perspectives that we don’t. I think we can all agree that collaboration is a good thing and that our combined thinking is greater than the sum of its parts. Why, then, do we feel the need to take a different view when it comes to working with artificial intelligence?
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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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.
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