💻 For real-time updates on events, connections & resources, join our community on WhatsApp: [ Ссылка ]
Looking to get started with Image Classification and CNNs? Here's a 2 hour, beginner-friendly tutorial on introduction to convolutions, kernels and features maps, working with images from the CIFAR10 dataset and much more. This lecture is part 4/6 of the Deep Learning with PyTorch Free Certification course. To learn more visit [ Ссылка ]
Time Breaks:
00:00 Introduction
3:51 Exploring the CIFAR10 Dataset
22:14 Training and Validation Datasets
36:54 Defining the CNN Model
1:21:46 Training the Model
1:42:10 Testing with Individual Images
1:45:40 Saving and Loading the Mode
1:47:37 Quick Recap and Further Reading/Exercises
1:51:15 Course Project - Train a Deep Learning Model from Scratch
1:55:50 Course Overview
1:56:34 What to do next?
Code and Resources:
🔗 Image Classification using CNNs: [ Ссылка ]
🔗 Classifying images of everyday objects using a neural network: [ Ссылка ]
🔗 Discussion forum: [ Ссылка ]
Topics covered in this video:
⌨️ Working with the 3-channel RGB images from the CIFAR10 dataset
⌨️ Introduction to Convolutions, kernels & features maps
⌨️ Underfitting, overfitting, and techniques to improve model performance
Deep Learning with PyTorch: Zero to GANs is a beginner-friendly online course offering a practical and coding-focused introduction to deep learning using the PyTorch framework.
You can learn more and register for a Free Certificate of Accomplishment at [ Ссылка ].
This course is taught by Aakash N S, co-founder & CEO of Jovian - a platform for sharing, showcasing and collaborating on data science projects online.
--
Learn Data Science the right way at [ Ссылка ]
Interact with a global community of like-minded learners [ Ссылка ]
Get the latest news and updates on Machine Learning at [ Ссылка ]
Connect with us professionally on [ Ссылка ]
Subscribe for new videos on Artificial Intelligence [ Ссылка ]
#CNN #PyTorch #DeepLearning #DataScience #MachineLearning #ImageClassification #GradientDescent #Certification #Course
