Google Colab or also called Colaboratory is a cloud service, offered by for free. It is based on the Jupyter Notebook environment. and is intended for machine learning training and research.
This platform allows you to train machine learning models directly in the cloud. Its installation on the computer is not necessary, so the computing resources can be used for other tasks.
If you want to know what Google Colaboratory is about You are going to have to continue reading this post, because we will talk 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 used to quickly train and test different machine learning models without having material restrictions. Its particularity is that anyone can use it. It is free and makes it easy to get started in deep learning and collaborate with your colleagues on computer data science projects. You can do this because collab it is a notebook environment free jupyter and that it runs completely in the cloud.
The most important thing is that it does not require configuration and the notebooks that 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:
- Write and run code on python.
- Keep record codes that support mathematical equations.
- create and share notebooks.
- Import and save files since
- Import and publish notebooks since Github.
- Use the GPUs of Google.
What are the unique features that make Google Colab the best virtual machine environment?
The main features of Google Colab are:
- You don’t need additional configuration. All of Google Colab is online, so you don’t need to download any apps 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 environment most known to programmers.
- You have access to powerful Google hardware for free. This is best of all, because the code you run through Colab notebooks uses Google GPU and TPU resources, without affecting your PC’s performance.
- You have the option to save and share in and from the cloud all the notebooks 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
We will present below 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 make more radio out of your work. 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 feature is useful for accessing the files you have backed up 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 major 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 the opportunity to use Google’s GPU and TPU shouldn’t be missed.
- Link Colab to Github. In 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 disconnections for inactivity, so you’ll have to be vigilant if you don’t want to lose part of your work.
List of Best Alternative Virtual Machine Environments to Google Colaboratory
Google Colab it provides a way for your computer to not carry the burden of your operations. But there are also other platforms that can help you with 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 available and can be used for free. It is ideal for those who are just starting out in this data science area. supports programming languages Python 2, P3, F#, and R.
kaggle.com
It is an excellent platform it 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 deploy 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 Data Platform Notebooks
IBM Watson Studio is a platform designed by a Jupyter notebook environment which makes it interactive and intuitive in its 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 the work. 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. It can be installed on the computer through a package manager pip either county. If you want you can do it in the browser. It is characterized by being free and having a graphical interface that allows for quite interactive development.
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