Multi-Class Classification with Softmax in PyTorch | 2024

In this tutorial, we'll walk you through how to implement a multi-class classification model using PyTorch. We'll cover every step, from loading the Iris dataset to building a feedforward neural network, applying softmax for multi-class classification, and training the model with CrossEntropyLoss. This deep learning project is perfect for beginners aiming to master multi-class classification tasks and build foundational knowledge in neural networks.

You'll learn:

How to load and preprocess the Iris dataset
The role of softmax and CrossEntropyLoss in classification tasks
How to build and train a neural network using PyTorch
Model evaluation and accuracy calculation
Plotting the training loss to track model performance

Whether you're a beginner or intermediate learner, this video will help you deepen your understanding of deep learning with PyTorch. Make sure to follow along and practice the code to master multi-class classification tasks.

Keywords: Multi-Class Classification, PyTorch Tutorial, Softmax, Iris Dataset, CrossEntropyLoss, PyTorch Neural Networks, Deep Learning with PyTorch, Neural Network Training, PyTorch Beginner Tutorial, Multi-Class Classification PyTorch, Softmax Activation PyTorch, Deep Learning for Beginners, PyTorch Loss Functions, PyTorch Model Training

Видео Multi-Class Classification with Softmax in PyTorch | 2024 канала Install Skill