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Update core-concepts.md #7

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2 changes: 1 addition & 1 deletion getting-started/core-concepts.md
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Expand Up @@ -16,7 +16,7 @@ Unlike other machine learning or deep learning frameworks, DL4J treats the tasks

Before the algorithm can start learning, you have to prepare the data, even if you already have a trained model. Preparing data means loading it and putting it in the right shape and value range \(e.g. normalization, zero-mean and unit variance\). Building these processes from scratch is error prone, so use DataVec wherever possible.

Deeplearning4j works with a lot of different data types, such as images, CSV, plain text, images, audio, video and, pretty much any other data type you can think of.
Deeplearning4j works with a lot of different data types, such as images, CSV, plain text, audio, video and, pretty much any other data type you can think of.

To use DataVec, you will need one of the implementations of the [RecordReader](https://github.com/eclipse/deeplearning4j/blob/master/datavec/datavec-api/src/main/java/org/datavec/api/records/reader/RecordReader.java) interface along with the [RecordReaderDataSetIterator](https://github.com/eclipse/deeplearning4j/blob/master/deeplearning4j/deeplearning4j-data/deeplearning4j-datavec-iterators/src/main/java/org/deeplearning4j/datasets/datavec/RecordReaderDataSetIterator.java).

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