In this article, we are going to discuss AI Class 10 Advance Python comprehensive notes. In class 9, you learnt about the basics of python. So let us start AI Class 10 Advance Python notes.
Follow this link to access the study material for Artificial Intelligence class 9.
AI Class 10 Advance Python
Before starting AI Class 10 Advance Python, you need to just recall the Python concepts you learnt in class 9. So here I will provide a short tour for the same. So you have already worked with Python and Jupyter Notebook in class 9.
Introduction to AI Tools
Follow this link to understand to get the answers of these questions:
- AI tools for python
- What is Jupyter Notebook?
- How to access Jupyter Notebook?
- Anaconda Navigator
- Introduction to virtual environment
- How to create virtual environment
- Install Jupyter Notebook dependencies
Introduction to Python
In class 9, you learned the basics of Python. In this section of AI Class 10 Advance Python, we will take a quick walk-through of python basics. So let’s have a recap of it!
What is Python?
Read the following quick pointers related to python:
|1||One of the popular programming languages|
|2||Developed by Guido Van Rossum at Centrum Wiskunde & Informatica|
|3||It was first released in 1991|
|4||Python got the name from BBC comedy series from 1970s – “Monty Python’s Flying Circus”|
|5||It can be used to follow procedural approach and object-oriented approach|
Nowadays Python is the first choice of programmers, developers, data scientists, and many more. So the question comes in mind that why python? For an Answer just have a look at the following table:
|1||AI is trending technology of the future, which requires a programming knowledge|
|2||Python is the best suitable programming language for AI because of the following features :|
- Very easy to learn, read and maintain: The syntax of python is very easy. It has a simple line structure of a program with fewer symbols and brackets. So that attracts people to write code in Python.
- Provide a broad standard library: It supports a broad category of built-in libraries to do work, which reduces the efforts and saves time of developers.
- Interactive mode and script mode: It supports interactive mode and script mode that allows the easy process of testing and debugging.
- Portability and compatibility: Python can run on multiple platforms and operating systems with almost similar kinds of interfaces.
- Extendable: It provides a more efficient way to customize the code according to the need of the developer.
- Databases and Scalable: Python provides major support to the open-source and commercial databases along with a better structure and supprt.
Applications of Python
Python is used in large areas of application today. Some of them are as following:
- Website Development
- Application Development
- Business Application
- Games and 3D Graphics
- Database Access
- Software Development
Python in Jupyternotebook
Follow this link to read about the basics of Python covered in Artificial Intelligence Class 9. You will learn about:
- How to create a virtual environment using jupyter notebook?
- Parts of Jypter notebook window
- Writing a program using jupyter notebook
- Using print() function in python and printing multiple lines
Basics of Python
The next section of AI Class 10 Advance Python provides information regarding python fundamentals. Follow this link to know more about basics python.
Conditional and Iterative Statements
Follow this link for python conditional statements:
The python packages are a collection of codes or functions of modules of similar types. Python provides various open source packages to use in the programs. Follow these steps to use any package:
Python packages require installation before use. Follow these steps to use them:
- Open anaconda navigator and activate virtual environment
- Install numpy package by using this commands:
- conda install numpy
- Press y when asked to do so.
After pressing y, it will start the installation process. Wait until the process stops.
You can install multiple packages by writing packages name to gether. For example
conda install pandas matplotlib
After installation of packages, you need to import them into the program. You can import these modules by following ways:
- import numpy
- import numpy as np
- from numpy import array
- from numpy import arrat as arr
Python provides some readymade packages. They are:
- NumPy – It is used for numerical array and its functions. It is most useful when we are working with large data sets and requires calculations. It also provides large support for manipulations.
- OpenCV – It is mainly used for image processing and support various functions related to image manipulations.
- Matplotlib – It is used to represent the data in visualization mode. It helps user to visualize data to understand them.
- NLTK – It stands for Natural Language Tool Kit supports features related to textual data. It is used for Natural Language Processing.
- Pandas – Pandas is used to handle 1D and 2D data structures of python. There are two major data structure used with python. They are series and Dataframe which is supported by pandas.
That’s all from the advanced python AI class 10. We will see the practicals of Matplolib and Pandas later.
I hope you enjoyed this article.