Learn Gradio with an in-depth Gradio course to build and deploy machine learning demos, use pretrained models, and create interactive user interfaces and dashboards.

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Gradio is an open-source Python library that simplifies the process of creating user interfaces and applications for your machine learning models. With its intuitive interface, you can easily showcase your work and deploy applications. 

In this course, you will be introduced to all the key features of Gradio. You will learn the tools to create a user interface dashboard and deploy your application. Next, we will look at connecting to your machine learning models or using pretrained models like OpenAI and Hugging Face. Finally, you will have the opportunity to get hands-on experience by building your application.

After completing this course, you can rapidly build demos of machine learning models and leverage powerful existing models. As AI and ML applications continue to gain traction, mastering Gradio is an invaluable skill that can set you apart in the field.

Machine Learning Applications in Gradio

**(True or False)** Gradio components must be explicitly defined as an input or output in one of the parameters upon initialization since the preprocessing and postprocessing differ depending on whether it is an input or output.

(True or False) Gradio components must be explicitly defined as an input or output in one of the parameters upon initialization since the preprocessing and postprocessing differ depending on whether it is an input or output.

**(True or False)** There are usually multiple ways to instantiate a Gradio component, which differ in default values that are used for its parameters.


(True or False) There are usually multiple ways to instantiate a Gradio component, which differ in default values that are used for its parameters.

**(True or False)** The Gradio ```Image``` component supports uploading images only.

(True or False) The Gradio <code>Image</code> component supports uploading images only.

**(True or False)** Gradio components include a preprocessing and postprocessing step which converts between values in the UI and the Python functions in the backend.

(True or False) Gradio components include a preprocessing and postprocessing step which converts between values in the UI and the Python functions in the backend.

**(True or False)** The ```Interface``` class has three components; a function, inputs and outputs. The inputs and outputs can be literals (e.g. string) or Gradio components.

(True or False) The <code>Interface</code> class has three components; a function, inputs and outputs. The inputs and outputs can be literals (e.g. string) or Gradio components.

Test yourself on Gradio components with this quiz.

Getting Started with Gradio

Displaying Components in Gradio

Block Layouts in Gradio

Interactive Components in Gradio

Dashboarding with Gradio

Deploying Machine Learning Model in Gradio

Chatbots with Gradio

Integration with Hugging Face

Miscellaneous

Building a Prediction Model in Gradio

Final Assessment

Conclusion

Quiz: Displaying Components in Gradio