June 2018
Intermediate to advanced
276 pages
6h 26m
English
In the real world, data scientists do not find data to be as clean as the publicly available datasets. Real world data is stored by different means, and the data itself is shaped in different categories. Thus, machine learning practitioners need to build their own systems and pipelines to achieve their goals and train the models. A typical machine learning project respects the following architecture:

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