How To Debug Deep Learning Programs | A Simple Process Anybody Can Use
Dimensional mismatch problems in deep learning programs can be a pain to debug, but I’ll show you a simple and repeatable process for dealing with them head on.
This comes from an old issue in my github that turns out to be related to a version mismatch with PyTorch. Rather than tell the person to downgrade their install, I’ll show you guys how to fix the dimensional mismatch problem in just a few minutes. This process can be extended to debugging any computer software, python program, or deep learning issue.
Learn how to turn deep reinforcement learning papers into code:
Deep Q Learning:
Actor Critic Methods:
Curiosity Driven Deep Reinforcement Learning
Natural Language Processing from First Principles:
https://www.udemy.com/course/natural-language-processing-from-first-principles/?couponCode=NLP1-OCT-21Reinforcement Learning Fundamentals
Here are some books / courses I recommend (affiliate links):
Grokking Deep Learning in Motion: https://bit.ly/3fXHy8W
Grokking Deep Learning: https://bit.ly/3yJ14gT
Grokking Deep Reinforcement Learning: https://bit.ly/2VNAXql
Come hang out on Discord here:
#PyTorch #DeepLearning #Debugging