The foundations of NLP and Deep Learning

1. The foundations of NLP and Deep Learning: addressing the explosion of textual data.

Nowadays, over 70% of circulating data is text. Therefore, we need to find ways to process it and, more importantly, extract useful information from it. All the techniques used to achieve this goal are grouped under the term NLP (Natural Language Processing), which combines machine learning techniques and text data pre-processing.

We handle text data daily, and to name just a few, we have emails, social networks, web pages, SMS messages, and instant messaging. This enormous mass of data is just waiting to be harnessed.

Indeed, this text data can be harnessed to develop several types of applications.

• Sentence or document classification (i.e., sentiment analysis in a text).
• Machine translation.
• Speech synthesis.
• Conversational agent (i.e., customer service).
• Everything you want, or at least everything you can do.

As you can see, the list of applications we can create with textual data is as long as the size of the data itself, though maybe I’m exaggerating a bit here.

2. The Foundations of NLP and Deep Learning: Definition and Challenges

And what if we asked the greatest of scholars:

The foundations of NLP and Deep Learning They rely on advanced techniques of artificial intelligence and machine learning, enabling a machine to understand and process textual data efficiently.

Natural Language Processing (NLP), or automatic language processing, or even automatic language processing (NLP), is a multidisciplinary field involving linguistics, computer science, and artificial intelligence. It aims to create tools for processing natural language for various applications. It should not be confused with computational linguistics, which aims to understand languages through the use of computational tools. (Wikipedia)

In simpler terms, Natural Language Processing (NLP) is here to offer techniques and strategies to create these different applications, allowing a machine to be as efficient as a human in understanding the languages we use in our daily lives.

You might say it's an impossible mission!!!

But here's the thing, we have quite a few Tom Cruises in the world of NLP.

However, even Tom Cruise could fail in such a perilous mission, and for several reasons, such as the complexity and diversity of languages (grammar, conjugation, word composition, etc.). To make matters worse, there's the added challenge of being able to effectively automate the evaluation of such systems. In other words, we still need a human to assess the performance of these applications, like a chatbot interacting with a human.

All these challenges related to the processing of textual data inspired us to propose a series called... The NLP Kingdom with three seasons to explain in detail the techniques used to create applications that leverage textual data, so that anyone can roll up their sleeves in a kingdom as vast and full of challenges to solve.

3.The Foundations of NLP and Deep Learning explained in 'The NLP Kingdom'

The first season consists of three episodes. In this season, we will focus more on the preprocessing techniques used in the field of NLP, namely Flirting with NLP.

Season 1 :

• Épisode 1 : From text to word 
• Épisode 2 : From words to numbers 
• Épisode 3 : From numbers to insights

The second season, also consisting of 3 episodes, will take us deep into the intricacies of representing words as continuous vectors that capture both the semantic and syntactic representation of words, namely. Word Embedding.

Season 2 :

• Épisode 1 : Word2Vec
  • Part 1 : Skip-Gram
  • Part 2 : Continuous Bag Of Words (CBOW)
• Épisode 2 : Global Vectors (GloVe)
• Épisode 3 : Other Technics

The third and final season will use the narratives from the previous two to immerse us in the heart of a profound network of brilliant minds working behind the scenes to give ordinary people like us the tools to shine in the kingdom of NLP, namely. Deep NLP.

Season 3 :

• Épisode 1 : RNNs
• Épisode 2 : LSTMs
• Épisode 3 : GRUs
• Épisode 4 : Attention
• Épisode 5 : Seq2Seq models
• Épisode 6 : Beam Search VS Greedy Search

To conclude, the fondements du NLP et du Deep Learning allow us to transform the way we leverage textual data, thus opening up new possibilities for businesses and researchers.