HANDS-ON-LAB

CI or CD Pipeline for Bitcoin News Search Engine Project

Problem Statement

Build Bitcoin domain-specific embeddings using Word2vec and FastText in python (Link).

Then create a simple Streamlit app which uses the trained embeddings to produce a Bitcoin news search engine as explained in this project (Link).

Finally build a CI/CD pipeline for this app as explained in this project (Link)

Create a new Bitcoin embeddings github repository and upload all the necessary files for deployment.
Deploy the app on the EC2 instance using the github repo created (follow the process from the project video).
Setup the Jenkins server on the EC2 instance (follow the process from the project video).
Create and set up the update app job as explained in the project video.
Create data and code monitoring jobs and test the pipeline

Q1. How can I build Bitcoin domain-specific embeddings using Word2vec and FastText?

Follow the project link provided for detailed instructions and code examples.

Q2. What does the Streamlit app for the Bitcoin news search engine do?

The Streamlit app utilizes the trained embeddings to enable users to search for Bitcoin-related news articles.

Q3. How can I set up a CI/CD pipeline for the app?

Refer to the project link to learn how to set up a CI/CD pipeline for the Streamlit app using Jenkins.