AI as an API - Part 2 - Deploy an ML Model Rest API using Encryption, Docker, Keras, FastAPI & NoSQL

AI as an API - Part 2 - Deploy an ML Model Rest API using Encryption, Docker, Keras, FastAPI & NoSQL

PART 1: https://www.youtube.com/watch?v=56qQNcHJxyQ
Web Scraping with Python on a Schedule: https://www.youtube.com/watch?v=NyDT3KkscSk

Learn to create & deploy a deep learning algorithm into a production REST API using Python, Keras, FastAPI, & NoSQL.

⦿ Build a Spam Classifier with Keras (post): https://kirr.co/u2tpsc
⦿ UCI Datasets: https://archive.ics.uci.edu/ml/datasets.php
⦿ Project Tutorials: https://cfe.sh/projects
⦿ Sign up for DataStax AstraDB: https://dtsx.io/3lC4cWy
⦿ Reference Code: https://github.com/codingforentrepreneurs/AI-as-an-API-Course-Reference
⦿ Production Code: https://github.com/codingforentrepreneurs/AI-as-an-API
⦿ Subscribe: https://cfe.sh/youtube

00:00:00 Welcome to Part 2
00:00:22 Pick a Cloud Provider
00:02:32 Generate SSH Keys
00:06:10 Add SSH Key to Linode
00:07:51 Provision VM on Linode
00:13:22 SSH into VM
00:16:12 Install GIT & Python Pip
00:19:23 Clone Public Project
00:22:50 Clone Private Repo
00:28:42 Install Docker
00:33:29 Why We Use Docker
00:37:44 Add Dockerfile
00:46:16 Build Docker Project & Enter Docker Bash
00:53:03 Environment Variables & Entrypoint
01:02:59 Added Pypyr Pipelines
01:08:20 Securing a Directory with Cryptography
01:20:47 Resuable Encryption Module
01:29:39 Pipelines for Encryption & Decryption
01:36:08 Production Environment Updates
01:41:50 Final Considerations for Updating our Systems
01:50:44 Thank You and Next Steps

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