In this 1-hour long project-based course, you will learn how to create a digit recognition web application using streamlit. This project is divided into two stages. In the first stage, you are going to write the training pipeline in which you will load MNIST Handwritten dataset. You will write the training and validation functions in order to train and validate the dataset. Lastly, in this stage you will do inference. In the second stage, you will use the best trained model from the training pipeline and you will use that in your web app. You will create the web user interface using streamlit python library. In this web app a user will draw a digit and given that drawn digit, the best trained model will output the probabilities.
Create digit recognition web app with Streamlit
Taught in English
Instructor: Parth Dhameliya
Included with
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Recommended experience
What you'll learn
Create complete training pipeline
Create web app using streamlit
Skills you'll practice
Details to know
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About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction
Load MNIST Handwritten Dataset
Load Dataset into batches
Load model
Create train and eval function
Training Loop
Inference
Create a web app
Recommended experience
Prior programming experience in Python and basic pytorch. Theoretical knowledge of Convolutional Neural Network and Training process (Optimization)
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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
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