Learn how to build neural networks using PyTorch's Sequential class in this comprehensive 27-minute tutorial. Explore multiple methods for constructing Sequential networks, including code setup and implementation. Discover techniques for achieving consistent predictions by setting random seeds. Gain insights into the class definition approach for model building. Enhance your understanding of PyTorch and neural network architecture through practical examples and step-by-step guidance.
Overview
Syllabus
Welcome to DEEPLIZARD - Go to deeplizard.com for learning resources
What is the Sequential class
Code Setup
Building Sequential Networks: Way 1
Building Sequential Networks: Way 2
Getting the Same Predictions by Setting the Random Seed
Building Sequential Networks: Way 3
Class Definition Way of Building a Model
Collective Intelligence and the DEEPLIZARD HIVEMIND
Taught by
deeplizard
Related Courses
-
Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial
-
Intro to PyTorch and Neural Networks
-
PyTorch for Deep Learning & Machine Learning – Full Course
-
Intermediate Deep Learning with PyTorch
-
Neural Networks and Random Forests
-
Fully Connected Neural Networks with Keras
