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Axel Sirota

Transfer learning is one of the key concepts that leverages companies all over the world in their LLM strategy. This course will teach you how to create LLM powered models through transfer learning.

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Transfer learning is one of the key concepts that leverages companies all over the world in their LLM strategy. This course will teach you how to create LLM powered models through transfer learning.

Creating an NLP model from scratch is very complex and time consuming. Luckily, you can stand upon the shoulder of giants with Transfer Learning.

In this course, Working with Pre-trained NLP Models, you’ll gain the ability to apply pre-trained LLMs to your models.

First, you’ll explore what transfer learning is.

Next, you’ll discover how to leverage it with Hugging Face.

Finally, you’ll learn how to prevent overfitting and measure fairness.

When you’re finished with this course, you’ll have the skills and knowledge of using pre-trained models in NLP needed to create amazing models with very few code.

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What's inside

Syllabus

Course Overview
Introducing Transfer Learning
LLMs A La Carte

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches students how to create AI-powered models through transfer learning
Suitable for beginners in the field of NLP
Covers pre-trained LLMs, Hugging Face, overfitting, and fairness in NLP
Led by experienced instructors with expertise in NLP
Provides hands-on experience through practical exercises
Requires basic understanding of NLP concepts

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Working with Pre-trained NLP Models with these activities:
Find a Mentor with Experience in Transfer Learning
Connect with an expert who can guide and support you in your learning journey.
Browse courses on Transfer Learning
Show steps
  • Attend industry events and meetups.
  • Reach out to professionals on LinkedIn and Twitter.
Practice Transfer Learning Techniques
Practice using transfer learning techniques to improve your NLP models.
Browse courses on Transfer Learning
Show steps
  • Identify a dataset and task for your NLP model.
  • Choose a pre-trained NLP model.
  • Apply transfer learning techniques to your model.
  • Train and evaluate your model.
Follow Tutorials on Transfer Learning
Reinforce your knowledge of transfer learning techniques.
Browse courses on Transfer Learning
Show steps
  • Find tutorials on transfer learning.
  • Follow the tutorials and apply the techniques to your own projects.
Five other activities
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Show all eight activities
Join a Transfer Learning Study Group
Enhance your learning by collaborating and sharing knowledge with peers.
Browse courses on Transfer Learning
Show steps
  • Find or create a study group focused on transfer learning.
  • Meet regularly to discuss topics, share resources, and work on projects.
Participate in a Transfer Learning Competition
Test your skills and gain valuable feedback on your transfer learning approach.
Browse courses on Transfer Learning
Show steps
  • Find a transfer learning competition that aligns with your interests.
  • Study the competition rules and dataset.
  • Build a model using transfer learning techniques.
  • Submit your model to the competition.
Create a Blog Post on Transfer Learning
Share your understanding of transfer learning with others.
Browse courses on Transfer Learning
Show steps
  • Choose a topic related to transfer learning.
  • Research the topic and write a blog post.
  • Promote your blog post on social media.
Create a Transfer Learning Presentation
Demonstrate your understanding of transfer learning by creating a presentation.
Browse courses on Transfer Learning
Show steps
  • Choose a topic related to transfer learning.
  • Research the topic and create a presentation.
  • Present your presentation to your classmates or a wider audience.
Build an NLP Project using Transfer Learning
Apply your transfer learning knowledge to a real-world project.
Browse courses on Transfer Learning
Show steps
  • Identify a problem that you can solve using NLP.
  • Gather data and prepare it for your model.
  • Choose a pre-trained NLP model and apply transfer learning techniques.
  • Train and evaluate your model.
  • Deploy your model and use it to solve the problem you identified.

Career center

Learners who complete Working with Pre-trained NLP Models will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers work with pre-trained models as a core part of their day-to-day. This course will provide you with the skills needed to work with pre-trained NLP models, which are a type of machine learning model. The course will teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Machine Learning Engineer, and will help you build better and more accurate models.
Natural Language Processing Engineer
Natural Language Processing Engineers are responsible for developing and maintaining NLP models. This course will provide you with the skills needed to work with pre-trained NLP models, which are a type of NLP model that has been trained on a large dataset. The course will teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Natural Language Processing Engineer, and will help you build better and more accurate models.
Data Scientist
Data Scientists use machine learning and other techniques to extract insights from data. This course will provide you with the skills needed to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Data Scientist, and will help you build better and more accurate models.
Software Engineer
Software Engineers who work with NLP will find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Software Engineer who works with NLP.
Consultant
Consultants who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Consultant who works with NLP.
Professor
Professors who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Professor who works with NLP.
Technical Writer
Technical Writers who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Technical Writer who works with NLP.
Researcher
Researchers who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Researcher who works with NLP.
Writer
Writers who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Writer who works with NLP.
Sales Engineer
Sales Engineers who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Sales Engineer who works with NLP.
Journalist
Journalists who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Journalist who works with NLP.
Linguist
Linguists who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Linguist who works with NLP.
Business Analyst
Business Analysts who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Business Analyst who works with NLP.
Marketing Analyst
Marketing Analysts who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Marketing Analyst who works with NLP.
Product Manager
Product Managers who work with NLP may find this course helpful. The course will teach you how to work with pre-trained NLP models, which are a type of machine learning model that has been trained on a large dataset. The course will also teach you how to leverage Hugging Face, a popular platform for working with pre-trained NLP models. This skillset will be invaluable to you as a Product Manager who works with NLP.

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Working with Pre-trained NLP Models.
This comprehensive guide delves into the principles and practices of transfer learning for NLP, offering a comprehensive overview of the field.
This comprehensive guide focuses specifically on using the Hugging Face Transformers library, providing detailed instructions and examples for applying Transformers to various NLP tasks.
This classic textbook provides a comprehensive overview of speech and language processing, offering a broader perspective on the field.
This comprehensive textbook provides a broad overview of the field of NLP, offering a solid foundation for understanding the concepts and techniques discussed in the course.
Provides a comprehensive overview of deep learning for NLP. It covers the different types of deep learning models, as well as the challenges and opportunities associated with using deep learning for NLP tasks.
Provides a practical guide to using NLP for real-world applications. It covers the different steps involved in building an NLP pipeline, as well as the challenges and opportunities associated with deploying NLP models.
Provides a practical guide to using R for text mining. It covers the different steps involved in text mining, as well as the challenges and opportunities associated with using R for text mining tasks.
Provides a practical guide to using Scikit-Learn, Keras, and TensorFlow for machine learning. It covers the different steps involved in building a machine learning pipeline, as well as the challenges and opportunities associated with using these libraries.
Provides a comprehensive overview of deep learning. It covers the different types of deep learning models, as well as the challenges and opportunities associated with using deep learning for real-world applications.
Provides a practical guide to using PyTorch for NLP. It covers the different steps involved in building an NLP pipeline, as well as the challenges and opportunities associated with using PyTorch for NLP tasks.
Provides a practical guide to using Python for data analysis. It covers the different steps involved in data analysis, as well as the challenges and opportunities associated with using Python for data analysis tasks.
Provides a comprehensive overview of data science. It covers the different steps involved in data science, as well as the challenges and opportunities associated with using data science for real-world applications.
Provides a comprehensive overview of machine learning. It covers the different types of machine learning algorithms, as well as the challenges and opportunities associated with using machine learning for real-world applications.
Provides a comprehensive overview of machine learning from a probabilistic perspective. It covers the different types of machine learning algorithms, as well as the challenges and opportunities associated with using machine learning for real-world applications.

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