Course
Learn Text Classification with PyTorch
Learn how to use PyTorch in Python to build text classification models using neural networks and fine-tuning transformer models.
This course includes
This course includes
Skill level
IntermediateTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary1 hourProjects
1Prerequisites
2 coursesWe suggest you complete the following courses before you get started with Learn Text Classification with PyTorch:- Intro to PyTorch and Neural Networks
- PyTorch for Classification
About this course
In this course, you’ll learn to build and train text classification models using PyTorch, starting with simple architectures and progressing to deep learning models. You’ll fine-tune transformer models like BERT, handle complex classification tasks, and optimize model performance using transfer learning. Evaluation metrics will be used to measure model effectiveness.
Skills you'll gain
Neural network training
Transformer fine-tuning
Text classification
Natural Language Processing (NLP) with PyTorch
Syllabus
Text Classification with PyTorch
Learn how to use PyTorch in Python to build text classification models using neural networks and fine-tuning transformer models.
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Related resources
- Article
PyTorch vs TensorFlow: Choosing the Best Framework for Deep Learning
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Regression vs. Classification
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How to use PyTorch DataLoader: Custom Datasets, Transformations, and Efficient Techniques
Learn how PyTorch's DataLoader optimizes deep learning by managing data batching and transformations. Explore key features like custom datasets, parallel processing, and efficient loading techniques.
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Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
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