Create TFRecords Dataset and use it to train an ML model

Create TFRecords Dataset and use it to train an ML model

Create TFRecords Dataset and use it to train an ML model. In this article we will see how to store and read data of the following type :(i) Integer.(int64, uint8, etc.); (ii) Floats.; (iii) Strings.; (iv) Images.

Hi Geeks,

Hope you are well and safe.

In this story, you will learn about :

1. What are TFRecords?

2. How to save data as tfrecords files?

3. Extract TFRecord data.

4. How to use a dataset from tfrecord for training a model?

PS — If you are here just to get the code. Take it from here and enjoy!

What are TFRecords?

The TFRecord is a Tensorflow format that is used for storing a sequence of binary records. Other than sequential data, TFrecord can also be used for storing images and 1D vectors. In this article we will see how to store and read data of the following type :

(i) Integer.(int64, uint8, etc.)

(ii) Floats.

(iii) Strings.

(iv) Images.

TFRecord can only be read and written in a sequential manner. So, It is generally be used for sequential models like RNN, LSTM, etc. But that does not mean we can use it for sequential learning only.

image-processing tensor computer-vision tfrecord tensorflow

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