Generating Text with PyTorch
Learn how to use Python to build text generation models based on neural networks like RNNs and LSTMs in this PyTorch tutorial.
Skill level
IntermediateTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary1 hourProjects
1Prerequisites
1 courseWe suggest you complete the following courses before you get started with Generating Text with PyTorch:- Intro to PyTorch and Neural Networks
About this course
Get ready to start your journey into the exciting world of language models! In this course, you will learn how to build and train neural networks to generate human-like text in PyTorch, one of the most popular deep learning frameworks in Python. You will learn how to read and transform raw text into numerical representations called embeddings that can be used by a neural network to learn contextual relationships within the text and generate relevant text responses. You will also learn how special neural network architectures like RNNs and LSTMs can process and generate sequential data.
Skills you'll gain
Read and transform raw text using tokenization and embeddings
Understand recurrent neural networks and long-short term networks
Store and load sequential text data using PyTorch utility classes
Build and train neural networks to generate text
Syllabus
Generating Text with PyTorch
Learn how to use Python to build text generation models based on neural networks like RNNs and LSTMs in this PyTorch tutorial.
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Related resources
- Article
What are Neural Networks?
An artificial neural network is an interconnected group of nodes, an attempt to mimic to the vast network of neurons in a brain. - Article
Long Short Term Memory Networks
Long short-term memory networks (LSTMs) are often used in deep learning programs for natural language processing. - Article
Common Applications of Deep Learning
This article reviews some of deep learning's common applications.
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