Hello Shouters!! Today we will learn about a detailed introduction of google colab
As in the earlier blog, we have discussed about the basic theory of the machine learning, in this blog we will see some practical implementation of machine learning. If you haven’t gone through my previous blog, I will suggest you to visit INTRODUCTION TO MACHINE LEARNING.
As for any programming language, we need an IDE, like NetBeans for java, in machine learning also, we need an IDE. The programming language mostly used for machine learning is Python and we will also be using the same. So we can use any IDE which supports python.
But most of these IDE’s are offline and thus use resources(RAM and hard disk etc) of the computer itself which limits the performance as most of us are using CPU’s but the machine learning algorithms require large processors or RAM etc. Usually, it takes a lot of time to train a model(make a machine learning project) in computers.
Alternatively, there are various cloud-based IDE’s which have large processors and resources and can help us in training the model in less time and improving the performances. e.g. google colab and also amazon’s Pagemaker is a good option. In these blogs, we will use google colab, which is the host to Jupyter notebook. So it will be easy for the users who have worked on the Jupyter notebook for python earlier. For new users also, it is very easy to use. we will how…….
–Type google colab in google chrome and open the first link you get.
–Now choose NEW NOTEBOOK to open a notebook(IDE). To learn more about google colab, you can select CANCEL and now the basic page of it will be opened and you can learn more about colab from here.
–Now a notebook will be opened in front of you. On the left-hand side, click on the files sidebox.
–On the right top corner, wait for it to connect to its resources
–Now click on MOUNT DRIVE and select the drive account you want to connect to collab. Remember, in this step, we are connecting our drive to the colab. While making projects, we will upload our datasets on our drive and access the dataset on a drive from google colab.
–Now select CONNECT TO GOOGLE DRIVE.
–Now you will see that the drive has been connected to your google account.
–You can see, all your folders and subfolders of the drive by clicking on the drive.
In this blog, we have learned about the google colab and how to connect it to drive for accessing the dataset from the drive.
In the next blog, we will do some practical implementation of machine learning using pandas. Till then
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Frequently Asked Questions –
Yes, It is completely free.
Both have their own pros and cons. For this course, we will use google colab.
Google colab is hosted on the Jupyter notebook. It means the both are same.
Recommended Posts –
- PRACTICAL APPROACH TO MACHINE LEARNING
- INTRODUCTION TO PANDAS IN MACHINE LEARNING
- THE DATA CLEANING IN MACHINE LEARNING
- FIRST MACHINE LEARNING MODEL