Deep Learning for Natural Language Processing
Have you ever wondered how Deep Learning u0026amp; AI have revolutionized Natural Language Processing (NLP)? Throughout our 2-day Deep Learning u0026amp; AI for NLP course, you will learn fundamental concepts of working with textual data in the context of Machine Learning, why deep learned neural networks like transformers are the state-of-the-art for natural language processing, and how you can integrate and adopt foundational models for your specific use cases.u003cbru003eu003cbru003eBased on Xebia Data’s extensive experience in solving NLP problems, this practical 2-day course teaches you how to apply deep learning as the basis of all modern AI systems in a variety of NLP contexts, including text classification, text summarization, and question answering processing!u003cbru003e
Looking to upskill your team or organization?
Rozaliia will gladly help you further with custom training solutions for your organization.
u003cstrongu003eRozaliia Khafizovau003c/strongu003eu003cbru003eData and AI Training Advisor
What will you learn?
After the training, you will be able to:
Refresh the fundamentals of NLP: Neural networks and deep learning, word embeddings, and the history of NLP from traditional machine learning to modern transformers and their limitations.
How to utilize existing models to your text data for various tasks such as text classification, -generation and -translation.
Apply transfer learning to fine-tune existing models on your own datasets for optimal results.
Build a pipeline from raw text input to predictions or text generation.
Understand common hyperparameters such as top-k, top-p and temperature for text generation.
Use zero- and few shot learning to train your data, even when little or no labelled data is available.
Program
This training is for you, if:
You are eager to apply state-of-the-art language models to your text data problems.
You are looking for a practical course that focuses on application.
You are comfortable with Python and familiar with basic data science concepts (train vs. test set, etc.).
You have some familiarity with deep learning, though it’s not necessary.
This training is not for you, if:
You are looking for an introduction into Deep Learning (you may be interested in: u003cstrongu003eu003cuu003eIntroduction to Deep Learningu003c/uu003e u0026amp; AIu003c/strongu003e)
You are new to programming, Python and Data Science.
You are looking for a course specifically about generative AI (see our course: u003ca href=u0022https://academy.xebia.com/training/building-llm-applications/u0022u003eBuilding LLM Applicationsu003c/au003e)
You are interested in a non-technical introduction to generative AI (see our course: u003ca href=u0022https://academy.xebia.com/course-event/introduction-to-generative-ai-3/u0022u003eIntroduction to Generative AIu003c/au003e)
Why should I follow this training?
u003cstrongu003eLearn how to use the most available mode of information – Text – to gain better insights.u003c/strongu003e
Not only understand modern AI systems and their limitations, but be able to implement and adopt foundational models for your use case. u003cbru003e- u003cbru003eLearn today, apply tomorrow!
Learn how to deal with limited data using zero-shot and few-shot learning.
What else should I know?
After registering for this training, you will receive a confirmation email with practical information. A week before the training, we will ask you about any dietary requirements and share literature if you need to prepare.
See you soon!
All literature and course materials are included in the price.
Information on the software and tooling will be shared before the start date.
This is a technical course involving some extent of programming. You will need a laptop.
Online courses are delivered via Zoom or Microsoft Teams.
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