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PyTorch: Tensor, Dataset and Data Augmentation

BeginnerCourse

Data preparation plays a crucial role in effectively solving machine learning (ML) problems. PyTorch, a powerful deep learning framework, offers a plethora of tools to make data loading easy. The PyTorch: Tensor, Dataset and Data Augmentation course will provide you with a solid understanding of the basics and core principles of PyTorch, specifically focusing on tensor manipulation, dataset management, and data augmentation techniques.

4.6 (339 Reviews)

Language

  • English

Topic

  • Artificial Intelligence

Enrollment Count

  • 1.93K

Skills You Will Learn

  • Artificial Intelligence, PyTorch, Python

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 3 hours

Platform

  • SkillsNetwork

Last Update

  • March 14, 2025
About this Course

"PyTorch: Tensor, Dataset and Data Augmentation" course equips you with the essential skills to handle and transform data efficiently for machine learning tasks. In this course, students will delve into the essential aspects of working with tensors in PyTorch. They will learn how to efficiently manipulate tensors, perform mathematical operations, and leverage tensor-based operations for tasks like data preprocessing and model training. Through a series of lectures and hands-on exercises, you will gain a deep understanding of PyTorch's data loading capabilities,  PyTorch Dataset Object and learn how to preprocess and augment data to maximize model performance.

Syllabus 

  1. Overview of Tensors
  2. Tensors 1D
  3. Two-Dimensional Tensors
  4. Derivatives in PyTorch
  5. Simple Dataset
  6. Dataset and Data Augmentation

Recommended Skills Prior to Taking this Course

  • Basic knowledge of Python programming language.

Instructors

Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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Wojciech "Victor" Fulmyk

Data Scientist at IBM

As a data scientist at the Ecosystems Skills Network at IBM and a Ph.D. candidate in Economics at the University of Calgary, I bring a wealth of experience in unraveling complex problems through the lens of data. What sets me apart is my ability to seamlessly merge technical expertise with effective communication, translating intricate data findings into actionable insights for stakeholders at all levels. Follow my projects to learn data science principles, machine learning algorithms, and artificial intelligence agent implementations.

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Contributors

Artem Arutyunov

Data Scientist

Hey, Artem here! I am excited about answering new challenges with data science, machine learning and especially Reinforcement Learning. Love helping people to learn, and learn myself. Studying Math and Stats at University of Toronto, hit me up if you are from there as well.

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