This notebook is an altered version of the colab notebook on TensorFlow Hub which shows how to use the Universal Sentence Encoder for sentence similarity.
So you can follow along the original notebook and make changes in that or just use this as a separate notebook or colab notebook.
It contains examples of common operations you can perform on vectors in a Machine Learning context.
This notebook shows how we can visualize vectors in a 2d vector space
This notebook shows how we can encode housr price data as an input vector
This notebook shows how to generate sentence embeddings using a cool library that enables you to do this easily
This notebook contains an example of how we can use vectors to represent David Bowie lyrics as input to a Machine Learning model