Build Your First CNN with PyTorch: MNIST Image Classification Tutorial | HINDI

Description: Welcome to my PyTorch tutorial! In this video, we’ll walk through building your first Convolutional Neural Network (CNN) using PyTorch. We’ll train the model on the MNIST dataset, one of the most popular datasets for beginners, and learn how to classify handwritten digits. This tutorial is perfect for anyone getting started with deep learning and PyTorch.
In this tutorial, you’ll learn:

*How to set up a CNN for image classification using PyTorch.
*How to load and preprocess the MNIST dataset.
*Building CNN architecture with convolutional and fully connected layers.
*Training a CNN with Adam optimizer and CrossEntropy loss.
*Evaluating model accuracy and testing on unseen data.

By the end of this tutorial, you'll have a basic understanding of how to build and train a CNN model from scratch using PyTorch.

If you're new to machine learning, computer vision, or deep learning, this step-by-step tutorial is for you! Make sure to like and subscribe for more content like this. Stay tuned for the next video where we dive into more complex CNN architectures and data augmentation techniques!
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