Generate Synthetic Images with DCGANs in Keras from Coursera

In this hands-on project, you will learn about Generative Adversarial Networks (GANs) and you will build and train a Deep Convolutional GAN (DCGAN) with Keras to generate images of fashionable clothes. We will be using the Keras Sequential API with Tensorflow 2 as the backend.

In our GAN setup, we want to be able to sample from a complex, high-dimensional training distribution of the Fashion MNIST images. However, there is no direct way to sample from this distribution. The solution is to sample from a simpler distribution, such as Gaussian noise. We want the model to use the power of neural networks to learn a transformation from the simple distribution directly to the training distribution that we care about. The GAN consists of two adversarial players: a discriminator and a generator. We’re going to train the two players jointly in a minimax game theoretic formulation.

This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Keras pre-installed.

Notes:

- You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.

- This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

What's inside

Syllabus

Project: Generate Synthetic Images with DCGANs in Keras

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Developers knowledge of Generative Adversarial Networks (GANs) and ability to build and train a Deep Convolutional GAN (DCGAN) with Keras

Utilises Keras Sequential API with Tensorflow 2 as the backend, which are industry-standard tools

Provides hands-on experience through Rhyme, a platform designed for practical learning

Suitable for learners based in the North America region, with efforts underway to expand accessibility

Limited access to the cloud desktop (5 times)

Reviews summary

Well-received gan course

Learners say this course is a solid introduction to Generative Adversarial Networks (GANs), especially for those interested in implementing them in Keras. According to students, the course offers good, clear instruction, and a well-prepared curriculum. Learners also praise the instructor for being great and excellent.

Instructor is great

"Excellent instructor. Dense with content and comments explaining bits of code."

"Trainer was awesome "

"Great Course, Learned a lot. Thanks Snehan."

Engaging and useful projects

"Mostly likeable project & good"

"It was a great experience with the Guided projects"

"Quick and easy to follow, very informative as well!"

Good starting point

"It's a very good start to know more about GANs"

"A good basic understanding of DCGANS."

"Nice choice to start with the understanding of GANs."

Clear and concise instruction

"Very clear and concise instructions"

"Good way to start out implementing DCGANS!!"

"Very well explanation towards completion of the code."

Some room for improvements

"Still room for a lot of improvements, average material"

"I would choose to learn online rather than study this course. The course was not well-prepared."

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 Generate Synthetic Images with DCGANs in Keras with these activities:

Organize your course materials

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Keep your course materials organized for easy reference.

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Create a folder for your course materials.
Save all of your course materials in the folder.
Create a system for organizing your materials.

Review Generative Adversarial Networks by Ian Goodfellow

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Familiarize yourself with the theoretical foundations of GANs.

View Deep Learning (Adaptive Computation and Machine... on Amazon

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Read the first three chapters of the book.
Summarize the key concepts of GANs.
Identify the strengths and weaknesses of GANs.

Follow a tutorial on how to build a DCGAN in Keras

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Gain practical experience in building and training DCGANs.

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Find a tutorial on how to build a DCGAN in Keras.
Follow the tutorial step-by-step.
Modify the tutorial to train a DCGAN on your own dataset.

Four other activities

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Practice coding GANs in Keras

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Solidify your understanding of GANs by coding them yourself.

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Set up a Python environment with Keras installed.
Code a simple DCGAN in Keras.
Train the DCGAN on your own dataset.
Evaluate the performance of the DCGAN.

Create a blog post or video tutorial on how to build a DCGAN in Keras

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Deepen your understanding of GANs by teaching others how to build them.

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Choose a topic for your blog post or video tutorial.
Write or record your content.
Publish your content online.

Mentor other students in the course

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Reinforce your knowledge by helping others learn.

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Join the course discussion forum.
Answer questions from other students.
Provide feedback on other students' work.

Contribute to an open-source GAN project

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Apply your skills to a real-world project and gain experience working with others.

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Find an open-source GAN project to contribute to.
Identify an area where you can contribute.
Submit a pull request with your contribution.

Career center

Learners who complete Generate Synthetic Images with DCGANs in Keras will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists are increasingly in demand as companies of all sizes realize the value of using data to drive decision-making and product development. This course will provide you with the knowledge and skills you need to enter the field of Data Science, and to build and manage a DCGAN. While this course does not cover all advanced topics in Data Science, taking it will put you in a great position to pursue a career in this field. As a professional Data Scientist, you can expect to hold a great deal of responsibility and impact on your company's product and strategy.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers work to solve real-world problems using machine learning techniques. This course will help you build a foundation in Generative Adversarial Networks, which are a type of machine learning model. By completing this course, you will be well on your way to a successful career as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

AI Researcher

AI Researchers work to develop new AI technologies and techniques. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of AI model. By taking this course, you will be well on your way to a successful career as an AI Researcher.

See salaries and explore the career path for AI Researcher

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as a Data Analyst.

See salaries and explore the career path for Data Analyst

Software Engineer

Software Engineers are responsible for designing, developing, and maintaining software systems. This course will help you build a strong foundation in Generative Adversarial Networks, which are a type of deep learning model. By taking this course, you will be well on your way to a successful career as a Software Engineer.

See salaries and explore the career path for Software Engineer

Product Manager

Product Managers are responsible for planning, developing, and launching new products. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as a Product Manager.

See salaries and explore the career path for Product Manager

Data Engineer

Data Engineers are responsible for designing, building, and maintaining data systems. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as a Data Engineer.

See salaries and explore the career path for Data Engineer

Quantitative Analyst

Quantitative Analysts are responsible for developing and using mathematical and statistical models to analyze financial data. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as a Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries are responsible for assessing and managing financial risks. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as an Actuary.

See salaries and explore the career path for Actuary

Computer Scientist

Computer Scientists are responsible for designing and developing computer systems. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as a Computer Scientist.

See salaries and explore the career path for Computer Scientist

Software Developer

Software Developers are responsible for designing, coding, and testing software. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as a Software Developer.

See salaries and explore the career path for Software Developer

Data Science Manager

Data Science Managers are responsible for leading teams of data scientists and overseeing data science projects. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as a Data Science Manager.

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Statistician

Statisticians are responsible for collecting, analyzing, and interpreting data. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as a Statistician.

See salaries and explore the career path for Statistician

Business Analyst

Business Analysts are responsible for analyzing business processes and making recommendations for improvements. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as a Business Analyst.

See salaries and explore the career path for Business Analyst

Risk Analyst

Risk Analysts are responsible for identifying and assessing risks to a business. This course will provide you with a strong foundation in Generative Adversarial Networks, which are a type of deep learning model that can be used to generate synthetic data. By taking this course, you will be well on your way to a successful career as a Risk Analyst.

See salaries and explore the career path for Risk Analyst