Build with PyTorch

Create tensors and build a simple neural network while learning the core pieces of the PyTorch workflow.

Train Your First Model

Use loss, gradients, and an optimizer to train a linear regression model from data and improve its predictions.

Make Predictions Independently

Run your trained model on new data and understand how PyTorch moves from tensors to real predictions.

About the course

AICC’s partnership with Linuxademy.com gives learners access to practical technical education focused on building real skills through hands-on experience. In PyTorch Fundamentals, you will learn the foundations of PyTorch by building and training a simple linear regression model. You will work with tensors, understand shapes and dimensions, use CPU and GPU computation, create a neural network, measure loss, calculate gradients, and update the model through training. The course uses Python, PyTorch, CUDA, and Google Colab to provide a simple environment for learning. You can follow along and run the code yourself or watch the lessons to understand the complete PyTorch workflow. Linuxademy’s mission is to help people build independently with modern technology. This course focuses on understanding what your PyTorch code is doing so you can build, inspect, train, and use models with greater independence.

Curriculum

1 Chapter · 3 Lessons

    1. (Included in full purchase)

      PyTorch Overview

    2. (Included in full purchase)

      Build Your First PyTorch Tensor

    3. (Included in full purchase)

      Build A Linear Regression Model

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