Watch Data Science 101: Deploying your Machine Learning Model Video Tutorial

So you have built your machine learning model, so now what? In this video, I will share to you 4 approaches that you can use for deploying your machine learning model. I also share how I deploy my machine learning models in my own research work. 🌟 Buy me a coffee: https://www.buymeacoffee.com/dataprofessor ⭕ Timeline 1:08 Obtaining the final machine learning model 1:25 Deploying the machine learning (ML) model 1:37 ML model as a data product 1:47 Four approaches to ML model deployment 1:52 Deployment format to use depends on the use case 2:30 Save ML model as objects 2:41 In Python, we can save as a pickle object 2:44 In R, we can save as a RDS object 3:01 Transfer ML-derived rules to a custom function, then apply this to make prediction 3:28 Create API to receive input and make prediction 3:59 Embed ML model inside a web application 4:04 In Python, popular web framework includes: Django, Flask and Dash 4:10 In R we have Dash and Shiny 4:21 Dash and Shiny are suitable for making data-driven dashboard 4:28 Shiny code can be deployed on your own web server or shinyapps.io The idea for this video was suggested in a comment by seshendra vemuri ⭕ Playlist: Check out our other videos in the following playlists. ✅ Data Science 101: https://bit.ly/dataprofessor-ds101 ✅ Data Science YouTuber Podcast: https://bit.ly/datascience-youtuber-podcast ✅ Data Science Virtual Internship: https://bit.ly/dataprofessor-internship ✅ Bioinformatics: http://bit.ly/dataprofessor-bioinformatics ✅ Data Science Toolbox: https://bit.ly/dataprofessor-datasciencetoolbox ✅ Streamlit (Web App in Python): https://bit.ly/dataprofessor-streamlit ✅ Shiny (Web App in R): https://bit.ly/dataprofessor-shiny ✅ Google Colab Tips and Tricks: https://bit.ly/dataprofessor-google-colab ✅ Pandas Tips and Tricks: https://bit.ly/dataprofessor-pandas ✅ Python Data Science Project: https://bit.ly/dataprofessor-python-ds ✅ R Data Science Project: https://bit.ly/dataprofessor-r-ds ⭕ Subscribe: If you're new here, it would mean the world to me if you would consider subscribing to this channel. ✅ Subscribe: https://www.youtube.com/dataprofessor?sub_confirmation=1 ⭕ Recommended Tools: Kite is a FREE AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I've been using Kite and I love it! ✅ Check out Kite: https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=dataprofessor&utm_content=description-only ⭕ Recommended Books: ✅ Hands-On Machine Learning with Scikit-Learn : https://amzn.to/3hTKuTt ✅ Data Science from Scratch : https://amzn.to/3fO0JiZ ✅ Python Data Science Handbook : https://amzn.to/37Tvf8n ✅ R for Data Science : https://amzn.to/2YCPcgW ✅ Artificial Intelligence: The Insights You Need from Harvard Business Review: https://amzn.to/33jTdcv ✅ AI Superpowers: China, Silicon Valley, and the New World Order: https://amzn.to/3nghGrd ⭕ Stock photos, graphics and videos used on this channel: ✅ https://1.envato.market/c/2346717/628379/4662 ⭕ Follow us: ✅ Medium: http://bit.ly/chanin-medium ✅ FaceBook: http://facebook.com/dataprofessor/ ✅ Website: http://dataprofessor.org/ (Under construction) ✅ Twitter: https://twitter.com/thedataprof/ ✅ Instagram: https://www.instagram.com/data.professor/ ✅ LinkedIn: https://www.linkedin.com/in/chanin-nantasenamat/ ✅ GitHub 1: https://github.com/dataprofessor/ ✅ GitHub 2: https://github.com/chaninlab/ ⭕ Disclaimer: Recommended books and tools are affiliate links that gives me a portion of sales at no cost to you, which will contribute to the improvement of this channel's contents. #dataprofessor #machinelearning #modeldeployment #deployml #deploymachinelearning #datascienceproject #learnr #rprogramming #learnrprogramming #python #learnpython #shiny #dash #datascience #datamining #bigdata #datascienceworkshop #dataminingworkshop #dataminingtutorial #datasciencetutorial #ai #artificialintelligence #r