JetBrains AcademyYou'll gain a solid understanding of fields like machine translation, chatbot systems, automatic question answering, and sentiment analysis. You will also learn about recent innovative approaches, such as transformer-based large language models, which are currently widely applied in solving natural language processing tasks.
In this course, you will:
Master advanced engineering concepts through ambitious projects. Each project deepens your expertise and transforms you from an experienced engineer into an exceptional one.
Any serious NLP experiment requires data processing. In most cases, you use ready-made data, but sometimes you need to compile a corpus yourself. Depending on the task, you may also need certain information about your text: part-of-speech tags, named entities, statistical characteristics, and so on. In this project, you will learn how to convert raw text into a corpus for further research.
Let's train a very simple but fully connected neural network! In this project, we'll create the necessary metric functions and use custom feedforward and backpropagation methods and functions, all done by hand. The dataset for this project is Fashion-MNIST – no more boring number recognition.
Extracting keywords can help you get to the text meaning. Also, It can help you with splitting texts into different categories. In this project, you will learn how to extract relevant words from a collection of news stories. There are many different ways to do it, but we will focus on frequencies, part-of-speech search, and TF-IDF methods. Note that each method can yield the results with varying degrees of accuracy for different texts. In reality, it is always good to try various methods and choose the best.
