Discover how to streamline Deep Learning projects using PyTorch Lightning in this 22-minute tutorial. Explore the installation process and delve into the GoEmotions dataset by Google for emotion classification. Learn to set up a Google Colab notebook, analyze data, tokenize Reddit comments, and determine appropriate sequence lengths. Gain valuable insights into PyTorch Lightning's capabilities and prepare for future developments in the field of Deep Learning and Machine Learning.
Getting Started with PyTorch Lightning for Deep Learning
Overview
Syllabus
What is PyTorch Lightning?
GoEmotions dataset by Google
Setup Google Colab notebook
Exploring the data
Tokenizing a Reddit comment
Choosing sequence length
Coming up next
Taught by
Venelin Valkov
Related Courses
-
PyTorch for Deep Learning & Machine Learning – Full Course
-
Advanced PyTorch Techniques and Applications
-
Getting Started with NLP Deep Learning Using PyTorch and fastai
-
Deep Learning - Computer Vision for Beginners Using PyTorch
-
Multi-Label Classification on Unhealthy Comments - Finetuning RoBERTa with PyTorch - Coding Tutorial
-
Create YOLO Dataset for Custom Object Detection Using OpenCV, PyTorch, and Python Tutorial
