Basic Pytorch Tensor Manipulation for Machine Learning
|
Learn the basics of tensor manipulation in PyTorch, focusing on fundamental concepts for building machine learning applications.
Tensors form the fundamental building block of the PyTorch ecosystem. Various components, such as network layers, loss function, gradient descent, and optimizer rely on underlying tensor operations.
In this course, you will get a comprehensive overview of tensors starting with how to create one. You will learn the many different types of tensors as well as how to concatenate and manipulate them by selecting elements, changing the shape, and more.
By the end of this course, you will have a basic understanding of how to work with PyTorch tensors and what they allow you to do.
User Reviews
Be the first to review “Basic Pytorch Tensor Manipulation for Machine Learning”
Related Products
Introduction to Python for AI Programmers
Learn Python programming with a focus on applications in AI and machine learning development.
Artificial Intelligence
Gain a comprehensive understanding of artificial intelligence, its technologies, and its impact on various industries.
Building a Reproducible Model Workflow
Explore best practices for creating reproducible workflows in machine learning model development.
Building Generative AI Solutions with Vector Databases
Understand how to leverage vector databases in building efficient generative AI solutions.
Building a Custom OpenAI Chatbot
Learn to create and customize chatbots using OpenAI technology for improved user interaction and engagement.
Computer Vision
Study techniques and applications in computer vision for processing and interpreting visual data.
There are no reviews yet.