April 2018
Beginner to intermediate
282 pages
6h 52m
English
There are mainly two aspects to consider:
Both will act as constraints as you are developing your pipelines.
Let's think about the limitations that training and scoring time bring to the table. Requirements for training time will usually determine the algorithms that you will include in your candidate list. For example, logistic regression and Support Vector Machines (SVMs) are fast-to-train algorithms, and this might be important to you, especially if you are prototyping ideas quickly using big data. They are also fast when it comes to scoring. There are different implementations for both, and also different options are available for solvers, which make these two convenient for ...