pH Level Forecasting of Well Water Samples in Malawi

This project focuses on an End-to-End Project for Forecasting pH levels of water samples in Malawi, which was conducted by Leeds Beckett University.

Workflows

• Understanding the Problem Statement
• Exploratory data analysis
• Data Pre-Processing
• Model Training
• Pipelining
  • Data Ingestion
  • Data Transformation
  • Model Trainer
  • Prediction Pipelining

Running Instruction

Clone the Repository

https://github.com/fosetorico/pH_level_forecasting.git

Create a conda environment after opening the repository

conda create -n your-chosen-name python=3.10 -y

conda activate your-chosen-name

Install the requirements

pip install -r requirements.txt

Finally run the app

python app.py

Now,

open up you local host and port

AWS-CICD-Deployment-with-Github-Actions

With specific access:

1. EC2 access : It is virtual machine
2. ECR: Elastic Container registry to save your docker image in aws

Description: About the deployment

1. Build docker image of the source code
2. Push your docker image to ECR
3. Launch Your EC2 
4. Pull Your image from ECR in EC2
5. Lauch your docker image in EC2

Policy:

1. AmazonEC2ContainerRegistryFullAccess
2. AmazonEC2FullAccess

1. Login to AWS console.

2. Create IAM user for deployment

3. Create ECR repo to store/save docker image

4. Create EC2 machine (Ubuntu)

5. Open EC2 and Install docker in EC2 Machine:

6. Configure EC2 as self-hosted runner:

setting>actions>runner>new self hosted runner> choose os> then run command one by one

>>>Optinal<<<

sudo apt-get update -y

sudo apt-get upgrade

>>>Required<<<

curl -fsSL https://get.docker.com -o get-docker.sh

sudo sh get-docker.sh

sudo usermod -aG docker ubuntu

newgrp docker

7. Setup github secrets:

AWS_ACCESS_KEY_ID

AWS_SECRET_ACCESS_KEY

AWS_REGION

AWS_ECR_LOGIN_URI

ECR_REPOSITORY_NAME