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Machine Learning Model Deployment with Streamlit

Published 9/2023
Created by Marco Peixeiro
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 44 Lectures ( 7h 13m ) | Size: 3 GB
Deploy ML models with Streamlit and share your data science work with the world

Free Download What you'll learn
Understand the core concepts and features of Streamlit
Build interactive data-driven web applications to deploy your model
Master the advanced features and integrations in Streamlit
Apply the best practices and optimization techniques for Streamlit
Connect your Streamlit app to data sources
Deploy your Streamlit app for free
Requirements
A working knowledge of Python and machine learning is required.
This course focuses only on deploying models using Streamlit. We will not spend time explaining how the models work or how they are developed and trained.
A computer with Anaconda installed.
Your favourite text editor installed (I use VSCode)
Description
The complete course to deploy machine learning models using Streamlit. Build web applications powered by ML and AI and deploy them to share them with the world.This course will take you from the basics to deploying scalable applications powered by machine learning. To put your knowledge to the test, I have designed more than six capstone projects with full guided solutions.This course covers:Basics of StreamlitAdd interactive elements, like buttons, forms, sliders, input elements, etc.Display chartsCustomize the layout of your application Capstone project: build an interactive dashboardCachingPerformance enhancement with cachingBasic and advanced usage of cachingCapstone project: deploy a classification modelSession state managementAdd more interactivity and boost performance with session state managementBasic and advanced usage of session stateCapstone project: deploy a regression modelMultipage applicationsBuild large apps with multiple pagesCapstone project: train and rank classification modelsAuthenticationAdd a security layer with authenticationAdd login/logout componentsAdvanced authentication with user management, reset password, etc.Capstone project: deploy a clustering model for marketingConnect to data sourcesConnect to databasesAccess data through APIsCapstone project: Deploy a sales demand modelDeploymentDeploy a Streamlit app for freeAdvanced deployment process with secrets management and environment variables
Who this course is for
Data scientists and machine learning engineers looking to deploy ML models and dashboards.
Homepage

https://www.udemy.com/course/machine-learning-model-deployment-with-streamlit/

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Machine Learning Model Deployment with Streamlit

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