An Easy Explanation Introduction to Tools For AI Class 10

In this article, you will read about An Easy Explanation Introduction to Tools For AI Class 10. So as you learnt some basic programming skills in class 9 with python. In this article we will discuss about some tools used for AI for data science. So here we start!

Introduction to Tools For AI Class 10

In this section of An Easy Explanation Introduction to Tools For AI Class 10 you will learn about some tools which are helpful for better understanding, debugging code, and many more.

As you learn about 3 major AI Domains: Data, NLP and CV require various packages needs to be installed. You can install them in IDLE too, but it is very difficult to manage them. So in this article we will discuss about anaconda and jupyter notebook.

Anaconda Distribution

The anaconda distribution is the collection of certain packages that are used for data science, R language, machine learning, and other platforms. It is one of the IDE software with integration of multiple platforms.

Before downloading check your OS version whether it is 32 bit or 64 bit. To download Anaconda follow this link:

Anaconda provides following applications:

1. CMD.exe prompt
2. Datalore
3. IBM Watson Studio Cloud
4. Jupyter lab
5. Jupyter Notebook
6. Powershell Prompt
7. Qt Console
8. Spyder
9. Glueviz
10. Orange 3
11. Pycharm professional
12. RStudio

These all applications run on base (root). It is suggested that you have to use jupyter notebook for the python introduction part in class 9 and Advanced Python in class 10. So in the next section of Introduction to Tools For AI Class 10, you will learn how to open jupyter notebook and how to work on it.

Introduction to Jupyter Notebook

The jupyter notebook is an integrated web application in anaconda distribution. It allows to create and share the live documents that contain live code, equations etc. If it is not integrated in your anaconda installations, you can find the installation guide by following this link:

The Jupyter Notebook is an incredibly powerful tool for interactively developing and presenting AI-related projects. The Jupyter project is the successor to the earlier IPython Notebook, which was first published as a prototype in 2010. Although it is possible to use many different programming languages within Jupyter Notebooks, Python remains the most commonly used language for it.

How to access jupyter notebook?

Anaconda provides the easiest way to access jupyter notebook. Anaconda navigator application provides you different application under one root. There are two ways to access jupyter notebook:

1. Anaconda Navigator
2. Anaconda Prompt

Anaconda navigator

This is a GUI based application that provides a way to launch jupyter notebook. Follow these steps to launch jupyter notebook.

1. Click Start > Anaconda3 > Anaconda Navigator(Anaconda3). It will open the Anaconda Navigator application.
2. Scroll and Find the Jupyter notebook.
3. Click on the launch button.

Observe these screenshots:

Anaconda Prompt

To launch jupyter notebook using Anaconda Prompt is a little bit different process then launching jupyter notebook through anaconda navigator. Anaconda prompt allows to launch jupyter notebook through the kernel and IPython is the default kernel for jupyter notebook. So this kernel is required to be installed inside the virtual environment.

Introduction to the virtual environment

A virtual environment is a tool that helps to keep dependencies required by different projects separated, by creating isolated Python virtual environments for them. This is one of the most important tools that most of the Python developers use.

Mostly it is used to avoid the conflict between multiple environments of the same programing language. A developer might need to work on Python 3.7 and Python 3.8 both. Now, in this case, a developer has to create a virtual environment so it will not affect the base environment and its dependencies. When a virtual environment is created, it will isolate the dependencies from the base environment.

How to create a virtual environment with anaconda distribution?

Create a virtual environment with Anaconda is very easy process. Follow these steps:

[1] Click on Start > Ananconda3(64-bit) > Anaconda Prompt(Anaconda3).

Or simply type Anaconda Prompt in the start menu search box and select Anaconda Prompt when it will display the list.

[2] Now the Anaconda prompt will open and you can find a word base is written before the user directory path. Observe the following screenshot.

[3] Now type the command to create virtual environment: conda create -n env python=3.8

[4] Now, it will ask to process ([y]/n)? Press y, and it will download some required packages then ask o activate the virtual environment. Type the command conda activate env. Observe the below-given screenshot:

[5] Now you can observe that the base word will be replaced by env. Observe this screenshot:

Install Jupyter notebook dependencies

To install jupyter notebook dependencies you need to type this command in active virtual environment:

conda install ipykernel nb_conda jupyter

It will again ask for yes/no proceed after sometime, press y and process ahead. It’s done.

Virtual environment and anaconda navigator is having many packages, so if you are getting any error kindly register yourself with online community you may get the your error solved there in the specific forum.

So I hope you learn about Introduction to Tools For AI Class 10 from this article very well. If you have anything from you are welcome through the comment section.

Thank you for reading this article.

Watch this video for more understanding:

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