Channel: CodingEntrepreneurs

Category: Education

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Description: AI as an API - Part 1 - Turn a ML Trained Model into an Rest API using Keras, FastAPI & NoSQL PART 2: youtu.be/nTdMjFcK3SM 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): kirr.co/u2tpsc ⦿ UCI Datasets: archive.ics.uci.edu/ml/datasets.php ⦿ Project Tutorials: cfe.sh/projects ⦿ Sign up for DataStax AstraDB: dtsx.io/3lC4cWy ⦿ Reference Code: github.com/codingforentrepreneurs/AI-as-an-API-Course-Reference ⦿ Production Code: github.com/codingforentrepreneurs/AI-as-an-API ⦿ Subscribe: 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