In this article, we look forward to answering some of the most commonly asked questions about Artificial Intelligence. The aim is to answer both aspects, including all the practical points, and clarify any doubts an individual may have concerning this topic.
Artificial Intelligence is one of the major talking points of our century. The capabilities and limitless potential of AI lead to several fun conversations and debates.
The rise in the popularity of Artificial Intelligence welcomes a lot of new eyes to AI. It ranges from enthusiasts with a growing passion for learning more about AI to aspirants looking forward to exploring the field or just other people who want to criticize it. But, regardless of which spectrum you lie on, there are several questions that run through your mind.
In this article, we look forward to answering some of the most commonly asked questions about Artificial Intelligence. The aim is to answer both aspects, including all the practical points, and clarify any doubts an individual may have concerning this topic. Let us briefly look at the various questions that we will try to tackle in this post today.
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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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.
What is the difference between machine learning and artificial intelligence and deep learning? Supervised learning is best for classification and regressions Machine Learning models. You can read more about them in this article.
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.