MrBryanBell / predict-co2-emissions

Predict CO2 Emissions

What if we could combine the power of machine learning and the speed of Go?

In this practice i will to predict CO2 Emissions using a multiple linear regression model and implement the model in Go.

$$y = \theta_0 + \theta_1 x_1 + \theta_2 x_2 + \cdots + \theta_n x_n$$

First i will analyze the data, get some insights and get the best features to use in the model. I will build the model in a jupyter notebook to analyze the results and compare function loss and accuracy.

Finally i will implement the model in Go thru a REST API using Gin.

This experiment will be helpful for a current project that i'm working on.

TODO

• Add an explanation of each column of the dataframe in analyzing-data.ipynb
• Update README.md in main directory:
  • Add some chart-images from any notebooks of the project.
  • Add some code blocks in markdown of how to make the http request and how does the endpoint will look.
  • Add instructions to reproduce Go-API using the docker-compose file.