Embedded Files
Before you start:
π Complete the pre-class exercise. [30 min]Β
π Download the class slides here.
1. Small Language Models
1. Small Language Models
In the previous class, we learned how to predict "the next word". Now, we focus our attention on small language models, and specifically n-gram models.
2. Contextual Word Embeddings
2. Contextual Word Embeddings
How can a model understand the essence and context of a word? In this video, we explore word embeddings and their importance in language models.
3. Deep Neural Networks - Part I
3. Deep Neural Networks - Part I
Let's dive deeper: in this video, we'll get inspiration from biological neurons to understand how artificial neurons in deep neural networks communicate information between each other.
4. Deep Neural Networks - Part II
4. Deep Neural Networks - Part II
Architectures, weights, activations: in this video, we go into the details of how this large models work and unpack the training process (warning: cute cats and dogs are involved).Β
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