Join us for a free workshop!
Introduction to Natural Language Processing
Wednesday, July 19, 2023
Constructor Learning, Heinrichstrasse 200, 8005 Zürich
6:30 - 8:30 PM
Free workshop, register today!
What is Natural Language Processing (NLP)?
Natural Language Processing is a field of artificial intelligence that focuses on the interaction between computers and human language. It enables computers to understand, interpret, and generate human language, allowing for advanced text analysis, sentiment analysis, language translation, chatbots, and much more.
Why learn Natural Language Processing?
Empower your business: Gain a competitive edge by leveraging NLP to extract valuable insights from vast amounts of textual data. Unlock the power of customer feedback, social media data, and customer support interactions to drive data-driven decision-making.
Enhance user experience: Take your applications to the next level by incorporating NLP capabilities. Develop intelligent chatbots, virtual assistants, and recommendation systems that can understand and respond to user queries naturally, providing a personalized and seamless user experience.
Advance your career: NLP is a rapidly growing field with immense career opportunities. By mastering NLP techniques and algorithms, you can open doors to exciting roles such as NLP engineer, data scientist, AI researcher, and more.
Is this event right for me?
Our NLP workshop is tailored for professionals and enthusiasts from various backgrounds:
- Data scientists and analysts broaden their skill sets.
- Software developers that want to add NLP capabilities to their programs.
- Language specialists and linguists looking to use their knowledge of computational linguistics.
- Researchers and AI enthusiasts who are enthusiastic about improvements in natural language generation and understanding.
- Anybody interested in learning more about NLP
What you will learn
- Sentence classification (Sentiment Analysis): Indicate if the overall sentence is either positive or negative, i.e. binary classification task or logistic regression task.
- Token classification (Named Entity Recognition, Part-of-Speech tagging): For each sub-entities (tokens) in the input, assign them a label, i.e. classification task.
- Question-answering: Provided a tuple (question, context) the model should find the span of text in the content answering the question.
- Mask-filling: Suggest possible word(s) to fill the masked input with respect to the provided context.
- Summarization: Summarize the input article into a shorter article.
- Translation: Translates the input from one language to another language.
- Feature extraction: Maps the input to a higher, multi-dimensional space learned from the data.
Agenda
- 6:30 - 7:00 PM: Welcome and Info Constructor
- 7:00 - 7:30 PM: The fundamentals of NLP
- 7:30 - 7:45 PM: Movie recommender system
- 7:45 - 8:00 PM: Multi-task NLP with transformers
- 8:00 - 8:30 PM: Q&A session
- 8:30 PM onwards: Apèro, snacks, and networking session
Learn from industry experts
Gain valuable insights from industry and elevate your knowledge
Dipanjan (DJ) Sarkar
Lead Data Scientist & Instructor
Albin Plathottathil
Data Science Consultant
Ekaterina Butyugina
Data Science Program manager
Marc Neuber
Business Developer & Chief Student Officer
Register today
Take advantage of this exciting opportunity
Don't let this incredible opportunity slip away to broaden your understanding and expertise in natural language processing. Reserve your seat today and take the first step towards becoming a specialist in this fascinating field. Register now and embark on an exciting journey to achieve your goals!
