Image Classification with PyTorch from Pluralsight

This course covers the parts of building enterprise-grade image classification systems like image pre-processing, picking between CNNs and DNNs, calculating output dimensions of CNNs, and leveraging pre-trained models using PyTorch transfer learning.

Perhaps the most ground-breaking advances in machine learnings have come from applying machine learning to classification problems. In this course, Image Classification with PyTorch, you will gain the ability to design and implement image classifications using PyTorch, which is fast emerging as a popular choice for building deep learning models owing to its flexibility, ease-of-use and built-in support for optimized hardware such as GPUs. First, you will learn how images can be represented as 4-D tensors and then pre-processed to get the best out of ML algorithms. Next, you will discover how to implement image classification using Dense Neural Networks; you will then understand and overcome the associated pitfalls using Convolutional Neural Networks (CNNs). Finally, you will round out the course by understanding and using the most powerful and popular CNN architectures such as VGG, AlexNet, DenseNet and so on, and leveraging PyTorch’s support for transfer learning. When you’re finished with this course, you will have the skills and knowledge to design and implement efficient and powerful image classification solutions using a range of neural network architectures in PyTorch.

What's inside

Syllabus

Course Overview

Preprocessing Images to Use in Machine Learning Models

Understanding the Drawbacks of Using Deep Neural Networks with Images

Introducing Convolutional Neural Networks

Building Convolutional Neural Networks for Image Classification

Optimizing Image Classification with Hyperparameter Tuning

Performing Image Classification with Pre-trained Models

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops skills in designing and implementing image classification solutions using neural network architectures in PyTorch, which is highly respected in the industry

Builds a strong foundation in image classification for beginners who want to begin learning this core skill

Taught by Janani Ravi, who is recognized for their work in the field of machine learning

Requires learners to have basic knowledge of machine learning and PyTorch, which may pose a barrier to some students

Focuses on image classification, which may not be relevant for learners interested in other aspects of machine learning

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Image Classification with PyTorch with these activities:

Compile a Glossary of Image Classification Terms

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Enhance your understanding of key concepts by creating a glossary of relevant terms, definitions, and examples.

Browse courses on Image Classification

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Identify important terms related to image classification.
Define each term clearly and concisely.
Include examples or illustrations to clarify the meanings of the terms.

Review Linear Algebra and Calculus

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Refresh your understanding of linear algebra and calculus concepts to strengthen your foundation for understanding CNNs and DNNs.

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Review matrices, vectors, and linear transformations.
Practice solving systems of linear equations.
Review derivatives and integrals.
Apply linear algebra and calculus concepts to solve problems related to image classification.

Review 'Deep Learning with PyTorch'

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Expand your knowledge and understanding of PyTorch and its applications in deep learning, particularly for image classification.

View Deep Learning with PyTorch: Build, train, and... on Amazon

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Read chapters related to image classification and CNNs.
Work through the provided code examples and exercises.
Apply the concepts to your own image classification projects.

Five other activities

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Participate in Peer Study Groups

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Engage with peers to discuss course concepts, share knowledge, and work through problems collaboratively, enhancing your understanding and retention.

Browse courses on Image Classification

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Find or form study groups with classmates.
Meet regularly to go over course material, solve problems, and ask questions.
Collaborate on projects and assignments to reinforce learning.

Follow Tutorials on CNNs and DNNs

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Supplement your understanding of CNNs and DNNs by following guided tutorials that provide step-by-step instructions and examples.

Browse courses on Convolutional Neural Networks

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Find reputable tutorials from sources like Coursera, Udemy, or YouTube.
Follow the tutorials and complete the exercises to gain hands-on experience.
Apply the techniques you learn to your own image classification projects.

Solve Image Classification Practice Problems

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Reinforce your understanding of image classification concepts and techniques by solving practice problems and exercises.

Browse courses on Image Classification

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Find practice problems on platforms like LeetCode or HackerRank.
Solve the problems using the techniques covered in the course.
Analyze your solutions and identify areas for improvement.

Design and Implement a Simple CNN for Image Classification

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Solidify your understanding of CNN architectures by designing and implementing a simple CNN from scratch to perform image classification.

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Define the architecture of your CNN, including the number of layers, filter sizes, and activation functions.
Train your CNN using a dataset of images.
Evaluate the performance of your CNN on a test set.
Optimize your CNN to improve its accuracy.

Participate in Image Classification Competitions

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Challenge yourself and test your skills by participating in image classification competitions, gaining valuable experience and showcasing your abilities.

Browse courses on Image Classification

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Identify relevant image classification competitions like Kaggle or DrivenData.
Download the competition dataset and familiarize yourself with the task.
Develop and train your image classification model.
Submit your model to the competition and track your progress.

Career center

Learners who complete Image Classification with PyTorch will develop knowledge and skills that may be useful to these careers:

Artificial Intelligence Engineer

Artificial Intelligence Engineers design and develop AI systems. Image classification is a fundamental skill for Artificial Intelligence Engineers, as it allows them to build models that can recognize and classify images. This course, Image Classification with PyTorch, provides a comprehensive overview of image classification techniques using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as an Artificial Intelligence Engineer.

See salaries and explore the career path for Artificial Intelligence Engineer

Computer Vision Engineer

Computer Vision Engineers design and develop systems that can see and interpret images. Image classification is a fundamental skill for Computer Vision Engineers, as it allows them to build models that can recognize and classify objects in images. This course, Image Classification with PyTorch, provides a comprehensive overview of image classification techniques using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Computer Vision Engineer.

See salaries and explore the career path for Computer Vision Engineer

Research Scientist

Research Scientists conduct research in various fields, including machine learning and computer vision. Image classification is a fundamental skill for Research Scientists, as it allows them to build models that can recognize and classify images. This course, Image Classification with PyTorch, provides a comprehensive overview of image classification techniques using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Research Scientist.

See salaries and explore the career path for Research Scientist

Deep Learning Engineer

Deep Learning Engineers bridge the gap between machine learning theory and practice. They use their knowledge of algorithms and coding to design and implement deep learning solutions to real-world problems. This course, Image Classification with PyTorch, provides a solid foundation in the fundamentals of image classification using PyTorch, a popular deep learning framework. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Deep Learning Engineer.

See salaries and explore the career path for Deep Learning Engineer

Data Scientist

Data Scientists play a vital role in organizations by extracting insights from data to solve business problems. Image classification is a fundamental skill for Data Scientists, as it allows them to analyze and interpret visual data. This course, Image Classification with PyTorch, provides a comprehensive overview of image classification techniques using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Data Scientist.

See salaries and explore the career path for Data Scientist

Robotics Engineer

Robotics Engineers design and develop robots. Image classification is a fundamental skill for Robotics Engineers, as it allows them to build robots that can recognize and classify objects in their environment. This course, Image Classification with PyTorch, provides a solid foundation in the fundamentals of image classification using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Robotics Engineer.

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Machine Learning Engineer

Machine Learning Engineers apply machine learning algorithms to solve real-world problems. Image classification is a fundamental skill for Machine Learning Engineers, as it allows them to build models that can recognize and classify images. This course, Image Classification with PyTorch, provides a comprehensive overview of image classification techniques using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

Software Engineers design, develop, and maintain software systems. With the increasing use of deep learning in various industries, Software Engineers with expertise in image classification are in high demand. This course, Image Classification with PyTorch, provides a solid foundation in the fundamentals of image classification using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Software Engineer.

See salaries and explore the career path for Software Engineer

Data Analyst

Data Analysts use data to solve business problems. Image classification is a valuable skill for Data Analysts, as it allows them to analyze and interpret visual data. This course, Image Classification with PyTorch, provides a solid foundation in the fundamentals of image classification using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Data Analyst.

See salaries and explore the career path for Data Analyst

Product Manager

Product Managers are responsible for the development and launch of new products. Image classification is a valuable skill for Product Managers, as it allows them to understand how users interact with visual content. This course, Image Classification with PyTorch, provides a solid foundation in the fundamentals of image classification using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Product Manager.

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UX Designer

UX Designers design user interfaces for websites and applications. Image classification is a valuable skill for UX Designers, as it allows them to understand how users interact with visual content. This course, Image Classification with PyTorch, provides a solid foundation in the fundamentals of image classification using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a UX Designer.

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Consultant

Consultants provide advice and guidance to organizations. Image classification is a valuable skill for Consultants, as it allows them to understand how businesses can use visual content to improve their operations. This course, Image Classification with PyTorch, provides a solid foundation in the fundamentals of image classification using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Consultant.

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Marketing Manager

Marketing Managers are responsible for developing and executing marketing campaigns. Image classification is a valuable skill for Marketing Managers, as it allows them to understand how consumers interact with visual content. This course, Image Classification with PyTorch, provides a solid foundation in the fundamentals of image classification using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Marketing Manager.

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Business Analyst

Business Analysts analyze business processes and identify opportunities for improvement. Image classification is a valuable skill for Business Analysts, as it allows them to understand how customers interact with visual content. This course, Image Classification with PyTorch, provides a solid foundation in the fundamentals of image classification using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Business Analyst.

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Project Manager

Project Managers plan and execute projects. Image classification is a valuable skill for Project Managers, as it allows them to understand how teams can use visual content to collaborate and track progress. This course, Image Classification with PyTorch, provides a solid foundation in the fundamentals of image classification using PyTorch. By completing this course, you will gain the skills and knowledge necessary to build and deploy image classification models, which can be valuable for a career as a Project Manager.

See salaries and explore the career path for Project Manager