Data Science is the art of combining data, science and technology to solve a business problem. There is a general misconception that Data Science is all about applying cool statistical/machine learning algorithms. However, Data Science involves several other critical steps before and after the use of statistical/machine learning algorithms. In this post, we will take a brief look at the life cycle of a data science project.
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Deep learning is a type of machine learning in which a model learns to perform classification tasks directly from images, text, or sound. Deep learning is usually implemented using a neural network architecture. The term “deep” refers to the number of layers in the network - the more layers, the deeper the network. Traditional neural networks contain only 2 or 3 layers, while deep networks can have hundreds.
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