Hey folks, today is a Mindblowing Monday 🤯!

Today I want to tell you about Language Models, a type of machine learning techniques that are behind most of the recent hype in natural language processing.

❓ Want to know more about them?

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A language model is a computational representation of human language that models which sentences are more likely to appear in a given language.

🎩 Formally, a language model is a probability distribution over the sentences in a language.

❓ What are they used for?

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⚙️ Language models allow computers to understand and manipulate language at least to some degree. They are used in machine translation, speech to text, optical character recognition, text generation, and many more applications!

They come in many flavors:

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⭐ The simplest language model is the *unigram model*, also called a *bag of words* (BOW).

In BOW, each word is assigned a probability Pi, and the probability of a sentence is computed assuming all words are independent. But of course, this isn' true.

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For example, "water" is a more commonly used word than "philosophy", but the phrase "philosophy is the mother of science" is arguably much more likely than the phrase "water is the mother of science".

💡 The likelihood of a phrase depends upon all its words.

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