Google Collab or also called Colaboratory is a cloud service, offered by Google for free. It is based on the Jupyter Notebook environment and is intended for machine learning training and research.
This platform allows training machine learning models directly in the cloud. It is not necessary to install it on the computer, so the computing resources can be used for other tasks.
If you want to know what Google Colaboratory is about you will have to continue reading this post, because we will tell you about its usefulness and the different functions it presents.
What is Google Colaboratory and what is this Google app for developers for?
Google Colab is a tool that is used to quickly train and test different models of automatic learning without having material restrictions. Its peculiarity is that anyone can use it. It is free and facilitates the possibility of getting started in Deep learning and collaborate with your colleagues on computer data science projects. You can achieve this because Colab it’s a notebook environment Free Jupyter and it runs entirely in the cloud.
The most important thing is that it does not require configuration and the notebooks you create can be edited simultaneously. by members of your own team. Colab supports many popular machine learning libraries that can be easily loaded onto your laptop.
Also, if you are a programmer, you will be able to do the following every time you use Google Colab:
- to write and run code in Python.
- Keep record codes that support mathematical equations.
- Create and share notebooks.
- Import and save files since Google drive
- Import and publish notebooks since Github.
- Use the GPU of Google.
What are the unique features that make Google Colab the best virtual machine environment?
The main features of Google Colab are:
- You do not need additional configuration. All Google Colab is online, so you do not need to download any application or configure anything on your computer.
- You can take advantage of Python libraries to develop, analyze, or visualize your projects. This is a point of great value since Python is the most popular environment for programmers.
- You have access to powerful Google hardware for free. This is the best of all, because the codes that you run through Colab notebooks use GPU and TPU resources from Google, without affecting the performance of your PC.
- You have the option to save and share in and from the cloud all the notebooks that you develop or run in Colab. You can do this if you link your Colab account with Google Drive and that’s it.
Learn how to get the most out of Google Colab and its virtual machines
Here are the best tips so that you can get the most out of Google Colab and its virtual machines:
- Save time with keyboard shortcuts. This is a great way to radio your work more. Pay attention to the large number of shortcuts available to you and try to use all of them. For this, you will have to enter the tab Tools and then click Keyboard shortcuts.
- Link your Google Drive with Colab. This function is useful to gain access to the files you have saved from anywhere and with any device that connects to your Drive. In this way, you will be able to consult your work at all times.
- Upload and download files from your computer with simple steps. You will realize that you can work with any file you have from your PC or from the cloud without great variations, you will only need a good Internet connection.
- Activate the GPU and TPU. You can use Google Colab with your own hardware resources, but you have the opportunity to use the GPU and the Google TPU should not be missed.
- Link Colab to Github. This way you will be able to open notebooks hosted on Github more easily.
- You should always be aware of the automatic disconnection of the 12 continuous hours that this tool has as default configuration. There are also 30 minute inactivity disconnects, so you should be vigilant if you don’t want to lose part of your work.
List of the best alternative virtual machine environments to Google Colaboratory
Google Colab Provides a way for your computer not to carry the burden of your operations. But there are also other platforms that can help you in this task. We will show you the best environments that create virtual machines and that are alternatives to Google Colaboratory.
Pay attention and choose the one that best suits your needs:
Notebooks.Azure.com
Microsoft Azure Notebooks it is very similar to Colab in terms of functionality. Both platforms have cloud sharing option available and can be used for free. It is ideal for those who are just starting out in this scientific area of data. Admits programming languages Python 2, P3, F # and R.
Kaggle.com
It is an excellent platform is also one of the products of Google. In it you will be able to find the source codes to work in data science. It has more than 19 thousand public data sets and more than 200 thousand public notebooks. Its use is free and you can join different competitions previously established by the platform.
Amazon SageMaker
Amazon SageMaker runs in the Jupyter Notebook application. It is intended for developers and data scientists who want to train and implement machine learning models. To access it, copy the following address “https://portal.aws.amazon.com”. You will have different types of learning instances. Its use is paid.
IBM DataPlatform Notebooks
IBM Watson Studio is a platform designed by a Jupyter notebook environment which makes it interactive and intuitive to use. You will be able to analyze data through Python, Scala and R languages, and unlike Google Colab, it has containers for multi-cloud deployment to store jobs. To access it, copy the following address “https://dataplatform.cloud.ibm.com”.
Jupyter.org
It is an open source web application whose purpose is create and share documents containing equations, visualizations, and text. Can be installed on the computer by means of a package manager pip or conda. If you wish, you can do it in the browser. It is characterized by being free and having a graphical interface that allows a fairly interactive development.