In this blog, I will introduce the features of Google Colaboratory.
- What is Google Colaboratory?
- Features of Google Colaboratory
- in conclusion
Google Colaboratory is a service provided by Google that allows you to write and execute Python directly from your browser. It’s like a Jupyter notebook environment stored on Google Drive where you can write, run and share code. A notebook document is made up of cells, and each cell can contain code, text, images, etc.
Google Colaboratory has the following three features.
- Can be used without building a Python development environment
- Easily share code with other users
- Free use of hardware features such as GPU and TPU
1. Can be used without building a Python development environment
In general, when trying to develop and run Python on a computer, you must first build the environment. For example, when using Jupyter Notebook, you first need to install tools such as Anaconda to prepare an environment where you can use Python, and then install Jupyter Notebook on your computer. Building this environment is especially difficult for programming beginners, and there are many cases where they stumble at this stage and cannot proceed further. However, if you use Google Colaboratory, you can use Python on your browser without having to build a troublesome and difficult environment, so you can easily run Python just by preparing a Google account.
2. Easily share code with other users
In general, when sharing a program file containing Python code with other users, you must attach it to an email and forward it. However, since Google Colaboratory notebooks are created on Google’s service, they can be easily shared with other Google users using the sharing function of Google Drive. You can also export your notebook to GitHub and share it. The created notebooks are saved in the Jupyter notebook format, and can be viewed and executed in compatible frameworks such as Jupyter notebooks. Therefore, it is possible to share files with people other than Google users who use Jupyter notebooks, etc.
3. You can use hardware functions such as GPU and TPU for free
Machine learning, which requires a large amount of data, requires hardware such as GPUs and TPUs for efficient learning. By using GPUs and TPUs, high-speed parallel processing is possible and model training time is greatly reduced. Using a GPU or TPU usually costs a few hundred yen per hour. Google Colaboratory allows you to use GPU and TPU for free under certain conditions. When using GPU or TPU, just switch to GPU or TPU in the setting tab, so it is very easy.
This time, I introduced the features of Google Colaboratory. It’s easy to get started without the hassle of setting up an environment, so if you want to try Python a little or build a machine learning model, why not take this opportunity to use it?
Skill Up AI is currently offering a related course, ” Introduction to Python for Machine Learning “.
In this course, we aim to be able to build a machine learning model using scikit-learn from a Python programming inexperienced level. Please consider it.
In addition, we hold a practical AI study session ” Skill Up AI Camp ” every Wednesday. At the study session, we also have hands-on sessions using Google Colaboratory (*Depending on the theme to be covered).
If you are interested, please join us!