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Hey there and welcome to this video! Today I will talk about the Embedding layer of PyTorch. Iamp;#39;m going to explain what it does and show you some common use cases and finally I will code up an example that implements a character level language model that can generate any text whatsoever. As you can see Iamp;#39;m on the official documentation of PyTorch and they describe the Embedding layer in the following way: amp;quot;Simple lookup table that stores embeddings of a fixed dictionary and sizeamp;quot;. What we can also see is that it has two positional arguments. One of them being the number of embeddings and the second one being the embeddings dimension. If I were to explain it in my own words eEmbedding is just a two-dimensional array wrapped in the module container with some additional functionality. Most importantly the rows represent different entities one wants to embed. So what do I mean by an entity? One very common example comes from th
