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Annotation 7553394019596

#data-science #infrastructure

Details of the life cycle will naturally vary between companies and projects: How you develop a predictive model for customer lifetime value differs greatly from building self-driving cars. However, all data science and machine learning projects have the following key elements in common:

1. From a technical point of view, all projects involve data and computation at their foundation.

2. This book focuses on practical applications of these techniques instead of pure research, so we expect that all projects will eventually need to address the question of integrating results into production systems, which typically involves a great deal of software engineering.

3. Finally, from the human point of view, all projects involve experimentation and iteration, which many consider to be the central activity of data science.
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Annotation 7584592563468

#RNN #ariadne #behaviour #consumer #deep-learning #priority #recurrent-neural-networks #retail #simulation #synthetic-data
RNNs can be applied to predict future consumer behavior in regression and classification settings, for example, to predict interest in fashion brands or consumer lifetime value.
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RNNs can be applied to predict future consumer behavior in regression and classification settings, for example, to predict interest in fashion brands or consumer lifetime value. We focus on predicting the probability P (ou | xu 1 , . . . , x u T ) of a consumer u to place an order ou , which we model as a binary classification problem. For instance, we could be

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Flashcard 7584597019916

Tags
#data-science #infrastructure
Question
An effective infrastructure helps to expose and manage [...] complexity, which is the natural state of the world we live in, while making a conscious effort to avoid introducing incidental complexity. Doing this well is hard and requires constant judgment.
Answer
inherent

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An effective infrastructure helps to expose and manage inherent complexity, which is the natural state of the world we live in, while making a conscious effort to avoid introducing incidental complexity. Doing this well is hard and requires constant

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