Implementing a Multi-Class CNN Image Classifier in Pytorch - Computer Vision Basics Ep. 3 CIFAR10 CNN
Offered By: rupert ai via YouTube
Course Description
Overview
Learn to implement a multi-class convolutional neural network (CNN) image classifier using PyTorch and the CIFAR-10 dataset. Follow along with this comprehensive 27-minute tutorial that covers data loading, model architecture design, training loop implementation, and model validation. Gain practical coding experience in Python and PyTorch while building a foundation for more advanced computer vision techniques. Explore topics such as CNN architecture, image classification, and model evaluation. Perfect for beginners looking to dive into deep learning and computer vision applications.
Syllabus
Intro:
Data loading recap:
Model architecture:
Training loop:
Testing our trained model on validation set:
Outro:
Taught by
rupert ai
Related Courses
Deep Learning with Python and PyTorch.IBM via edX Introduction to Machine Learning
Duke University via Coursera How Google does Machine Learning em Português Brasileiro
Google Cloud via Coursera Intro to Deep Learning with PyTorch
Facebook via Udacity Secure and Private AI
Facebook via Udacity