Building Transformer-Based Natural Language Processing Applications Training in Norway

  • Learn via: Classroom
  • Duration: 1 Day
  • Price: Please contact for booking options
We can host this training at your preferred location. Contact us!

Applications for natural language processing (NLP) have exploded in the past decade. With the proliferation of AI assistants and organizations infusing their businesses with more interactive human-machine experiences, understanding how NLP techniques can be used to manipulate, analyze, and generate text- based data is essential. Modern techniques can capture the nuance, context, and sophistication of language, just as humans do. And when designed correctly, developers can use these techniques to build powerful NLP applications that provide natural and seamless human-computer interactions within chatbots, AI voice agents, and more.
Deep learning models have gained widespread popularity for NLP because of their ability to accurately generalize over a range of contexts and languages. Transformer-based models, such as Bidirectional Encoder Representations from Transformers (BERT), have revolutionized NLP by offering accuracy comparable to human baselines on benchmarks like SQuAD for question-answer, entity recognition, intent recognition, sentiment analysis, and more.
In this workshop, you’ll learn how to use Transformer-based natural language processing models for text classification tasks, such as categorizing documents. You’ll also learn how to leverage Transformer-based models for named-entity recognition (NER) tasks and how to analyze various model features, constraints, and characteristics to determine which model is best suited for a particular use case based on metrics, domain specificity, and available resources.

Assessment type:


Skills-based coding assessments evaluate students’ ability to build an NLP task, including a neural module pipeline and training.
Multiple-choice questions evaluate students’ understanding of the NLP concepts presented in the class.

Certificate:


Upon successful completion of the assessments, participants will receive an NVIDIA Deep Learning Institute certificate to recognize their subject matter competency and support professional career growth
Why Choose NVIDIA Deep Learning Institute for Hands-On Training?
  • Access workshops from anywhere with just your desktop/laptop computer and an internet connection. Each participant will have access to a fully configured, GPU-accelerated workstation in the cloud.
  • Obtain hands-on experience with the most widely used, industry-standard software, tools, and frameworks.
  • Learn to build deep learning and accelerated computing applications for industries, such as healthcare, robotics, manufacturing, accelerated computing, and more.
  • Gain real-world expertise through content designed in collaboration with industry leaders, such as the Children’s Hospital of Los Angeles, Mayo Clinic, and PwC.
  • Earn an NVIDIA Deep Learning Institute certificate to demonstrate your subject matter competency and support your career growth.

  • Experience with Python coding and use of library functions and parameters
  • Fundamental understanding of a deep learning framework such as TensorFlow, PyTorch, or Keras
  • Basic understanding of neural networks

  • Understand how text embeddings have rapidly evolved in NLP tasks such as Word2Vec, recurrent neural network (RNN)-based embeddings, and Transformers
  • See how Transformer architecture features, especially self-attention, are used to create language models without RNNs
  • Use self-supervision to improve the Transformer architecture in BERT, Megatron, and other variants for superior NLP results
  • Leverage pre-trained, modern NLP models to solve multiple tasks such as text classification, NER, and question answering
  • Manage inference challenges and deploy refined models for live applications

Introduction
  • Meet the instructor.
  • Create an account at courses.nvidia.com/join
Introduction to Transformers
Explore how the Transformer architecture works in detail:
  • Build the Transformer architecture in PyTorch.
  • Calculate the self-attention matrix.
  • Translate English to German with a pre-trained Transformer model
Self-Supervision, BERT, and Beyond
Learn how to apply self-supervised Transformer-based models to concrete NLP tasks using NVIDIA NeMo:
  • Build a text classification project to classify abstracts.
  • Build a named-entity recognition (NER) project to identify disease names in text.
  • Improve project accuracy with domain-specific models.
Inference and Deployment for NLP
Learn how to deploy an NLP project for live inference on NVIDIA Triton:
  • Prepare the model for deployment.
  • Optimize the model with NVIDIA®
  • Ten s or R T™
  • Deploy the model and test it.
Final Review and Next Steps
  • Review key learnings and answer questions.
  • Complete the assessment and earn a certificate.
  • Take the workshop survey.
  • Learn how to set up your own environment and discuss additional resources and training.



Contact us for more detail about our trainings and for all other enquiries!

Upcoming Trainings

Join our public courses in our Norway facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom
23 juli 2024
Oslo, Bergen, Trondheim
1 Day
Classroom / Virtual Classroom
16 august 2024
Oslo, Bergen, Trondheim
1 Day
Classroom / Virtual Classroom
21 august 2024
Oslo, Bergen, Trondheim
1 Day
Classroom / Virtual Classroom
24 august 2024
Oslo, Bergen, Trondheim
1 Day
Classroom / Virtual Classroom
12 september 2024
Oslo, Bergen, Trondheim
1 Day
Classroom / Virtual Classroom
24 september 2024
Oslo, Bergen, Trondheim
1 Day
Classroom / Virtual Classroom
06 oktober 2024
Oslo, Bergen, Trondheim
1 Day
Classroom / Virtual Classroom
21 oktober 2024
Oslo, Bergen, Trondheim
1 Day
Building Transformer-Based Natural Language Processing Applications Training Course in Norway

The Nordic country Norway, is in Northern Europe. Known for its stunning natural beauty, including fjords, mountains, and forests, Norway is also famous for its high standard of living and strong social welfare system. Norway's capital and largest city is Oslo. Tromsø, Bergen, Trondheim and Stavanger are the other tourist attracting cities of Norway.

Norway is a constitutional monarchy with King Harald V as the head of state. The country has a population of 5,425,270 as of January 2022. Norway is a relatively small country and has a relatively low population density, with much of its land area covered by forests, mountains, and fjords. Despite its small size, Norway is known for its rich cultural heritage, strong economy, and stunning natural beauty, which attracts millions of visitors every year. This Nordic country is also known for its winter sports, such as skiing and snowboarding, and is a popular destination for outdoor enthusiasts.

Norway has a long history of invention and is home to numerous more top-tier tech firms and research facilities, such as; Kongsberg Gruppen, Telenor, Atea, Evry and Gjensidige Forsikring.

Due to the country's high latitude, there are large seasonal variations in daylight. From late May to late July, the sun never completely descends beneath the horizon. Which attracts many tourists around the world to see the "Land of the Midnight Sun". Tourists mainly visit Sognefjord, Norway's Largest Fjord, Pulpit Rock, one of the most photographed sites in Norway and of course the capital; Oslo.

Oslo is considered the business center of Norway. It is the country's largest city and the capital of Norway. The city is home to many of Norway's largest and most important companies, as well as several international organizations and research institutions. Additionally, the city is a popular tourist destination, known for its scenic location on the Oslo Fjord, its many museums and cultural attractions, and its vibrant nightlife and dining scene. Some of the most popular museums in Oslo are The Norwegian Museum of Cultural History, The Nobel Peace Center, The National Museum of Art, Architecture, and Design, The Munch Museum and The Vigeland Museum.
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