PyTorch for Deep Learning & Machine Learning – Full Course

What You Will Learn

• You will learn the foundations of machine learning and deep learning using PyTorch.
• You will understand how to write PyTorch code to implement machine learning concepts.
• You will be able to experiment with PyTorch code and run it to see the results.

Key Concepts

Machine learning is the process of turning data into numbers and finding patterns in those numbers using algorithms. Deep learning is a subset of machine learning that uses complex algorithms to find patterns in data. Artificial intelligence is the overarching topic that includes machine learning and deep learning. PyTorch is a machine learning framework written in Python that allows us to write code to implement machine learning concepts.

Code Examples

Unfortunately, there are no code snippets provided in the transcript that can be used as examples. The transcript only includes text that describes the content of the course and does not include any actual code.

Lesson Summary

In this lesson, you were introduced to the concept of machine learning and deep learning using PyTorch. You learned that machine learning is the process of turning data into numbers and finding patterns in those numbers using algorithms. You also learned that deep learning is a subset of machine learning that uses complex algorithms to find patterns in data. The lesson emphasized the importance of writing code to implement machine learning concepts and experimenting with PyTorch code to see the results. The instructor, Daniel Bourke, encouraged you to get hands-on and write lots of code to learn machine learning and deep learning. The lesson also provided resources for further learning, including an online readable book version of the course and additional chapters available at learn.pytorch.io.

Practice Exercise

Try installing PyTorch on your computer and running a simple PyTorch code snippet to get familiar with the framework. You can start with a basic example, such as creating a PyTorch tensor, and then experiment with different operations on the tensor.

What Is Next

In the next lesson, you will learn more about the basics of PyTorch and how to use it to implement machine learning concepts. You will start writing PyTorch code and experimenting with different examples to solidify your understanding of machine learning and deep learning.