AI as an API - Part 1 - Train an ML Model and turn it into an Rest API using Keras, FastAPI & NoSQL
AI as an API - Part 1 - Turn a ML Trained Model into an Rest API using Keras, FastAPI & NoSQL
PART 2: • AI as an API - Part 2 - Deploy an ML ...
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/datase...
⦿ Project Tutorials: https://cfe.sh/projects
⦿ Sign up for DataStax AstraDB: https://dtsx.io/3lC4cWy
⦿ Reference Code: https://github.com/codingforentrepren...
⦿ Production Code: https://github.com/codingforentrepren...
⦿ Subscribe: https://cfe.sh/youtube
0:00:00 - Welcome
00:00:32 - Demo
00:04:13 - Requirements
00:05:50 - Setup Project on VSCode
00:14:55 - Download Datasets
00:24:14 - Unzip Datasets
00:26:55 - Extract Review & Combine Dataset
00:42:46 - Convert Dataset into Vectors
00:58:26 - Split & Export Vectorized Dataset
01:09:43 - Training our Machine Learning Model
01:23:21 - Upload our Model to Object Storage
01:31:07 - Model Download Pipeline
01:49:10 - Base FastAPI App
01:56:05 - Load Keras Model into FastAPI
02:03:31 - Predictions with Keras & FastAPI
02:22:14 - Creating a Resuable AI Model Class
02:49:42 - AstraDB Keys, Pydantic Settings & Environment Variables
02:58:52 - Configure AstraDB Cluster & Session
03:08:20 - Cassandra Model in AstraDB
03:19:38 - Store inference data via Cassandra Model
03:23:28 - Paginate a Cassandra model as a FastAPI Streaming Response
03:38:47 - Ngrok, Pydantic Model, & Post Data
03:47:27 - Thank you
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