Do you want help getting involved in the future of data? Do you want to get involved in the exciting field of Machine Learning?
This tutorial will teach you the basics of how to get started- whether you are an expert data scientist, or a complete beginner.
In this tutorial, you will learn how to set up your own jupyter notebook using the fast.ai deep learning framework alongside Paperspace’s gradient platform. You will learn how to deal with some of the common bugs/errors that you can come across during the setup process.
What is fast.ai?
Fast.ai is a python library that aims to make AI and Deep Learning simpler to learn and get started. It runs on top of another python library called PyTorch and has within it many state of the art machine learning algorithms. One aim of fast.ai is to make deep learning as accessible as possible; the framework is designed so that you can set up a model in only a few lines of code.
Please visit the course website to view the free video lectures and chapters of the book.
What is Gradient?
Gradient is an “End-to-End machine learning pipeline” made by Paperspace. It is designed to allow you to complete ML projects from start to finish and allows you to run jupyter notebooks within a “container” on a free machine(GPU or CPU). A container is a development environment that contains all of the associated files that are necessary for a particular framework, such as fast.ai or TensorFlow.