The course will balance theoretical foundations with practical examples using the Python programming language.
No prior experience with libraries such as NLTK or scikit-learn is required for this course.
Having existing experience with Python will be extremely beneficial but not required: users of other programming languages and tools (including e.g. Java, C++, C#, JavaScript, Matlab, Excel or Rlang) will find this course beneficial.
Software engineers, data scientists, data analysts, researchers and students who want to get started with Natural Language Processing applications, with the purpose of extracting useful information from free-text data.
This first section provides the basic tools and techniques to get started with Natural Language Processing
This section aims at improving our understanding of a document, or a collection of documents, using techniques that go beyond simple word frequencies.
This section tackles the problem of classifying documents into a set of predefined categories.
The last section offers an outlook on advanced NLP problems, so delegates are equipped with ideas and techniques to tackle more specific applications
Classroom or Remote
Remote
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