Congratulations!, you have just created a Linear Regression Model using Julia's Flux.jl library. Hopefully this blog has helped you to understand the basics of Flux.jl library so that you can create your own personalized ML models from scratch. I am planning to create a series in which this blog is part one of that series. The other parts could include deploying this Regression Model using streamlit/flask and also developing Deep Learning models using the Flux.jl

Last time, I gave a quick introduction to the Julia programming language which has just reached the 1.0 release mark after ten years of development. Julia is touted as the next great thing for scientific computing, machine learning, data science and artificial intelligence. Its hope is to supplant Python which is currently the goto language in these fields. The goal is a more unified language, since it was developed well after Python and learned from a lot of its mistakes. It also claims to have the flexibility of Python but with the speed of a true compiled language like C. I saw that in the list of packages there was support for using Google's TensorFlow AI system natively from Julia so I thought I would give this a try.