Python for AI/ML – Episode 2

Understanding Python Basics for Artificial Intelligence and Machine Learning

In the previous episode, we successfully installed Python and set up the development environment required for Artificial Intelligence and Machine Learning projects. Now, in Episode 2, we will begin learning the fundamentals of Python programming that form the backbone of AI and ML development.

Python is one of the most popular programming languages in the world because of its simple syntax, readability, and massive collection of libraries. Most AI and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and Pandas are built using Python. Therefore, understanding Python basics is the first step toward becoming an AI/ML developer.

Why Python for AI and ML?

Python is widely used in AI and ML because:

Due to these advantages, companies and researchers prefer Python for building intelligent systems.

Writing Your First Python Program

The first program most beginners write is the “Hello World” program.

print("Hello World")

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Printing in Python

Printing means displaying output on the screen. Python uses the print() function to show messages, values, and results.

Syntax of print()

print("Hello")

Printing Text

Text must be written inside quotes.

Example

print("Hello World")

Output

Hello World

Printing Numbers

Numbers can be printed without quotes.

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image showing printing numbers in python

Variables in Python

Think of a variable as a labeled storage box. In Python, you use these boxes to store data so you can refer to it later by name.

Unlike some other languages, Python is "dynamically typed," which means you don’t have to tell the computer what kind of data is going inside the box ahead of time. You just give it a name and assign a value.

1. The Anatomy of a Variable

To create a variable, you follow a simple pattern: name = value.

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image showing variable types

Variable Properties

1. Variable Name Rules

A variable name:

Correct

Image

Wrong

1name = "Alex"student name = "Alex"

2. Case-Sensitive

Python treats uppercase and lowercase differently.

age = 20

Age = 30

Here:

3. No Reserved Keywords

Python keywords cannot be used as variable names.

Wrong

class = 10for = 5

Because:

are already used by Python.

4. No Spaces

Variable names cannot contain spaces.

Wrong

student name = "Chipset"

Correct

student_name = "Chipset"

Underscores _ are used instead of spaces.

5. Dynamic Typing

Python automatically decides the type of variable.

x = 10x = "Python"

First:

Later:

Python allows changing data types dynamically.

6. Memory Allocation

When a value is assigned to a variable, Python stores it in memory.

name = "AI"

Here:

2. Basic Data Types

Variables can hold different "flavors" of data. Here are the most common ones you'll use:

Image

an image on data types and their properties in python

1. Integer (int)

Integers are whole numbers.

x = 10

Properties

Examples

a = 100b = -25

2. Float (float)

Floats are decimal numbers.

pi = 3.14

Properties

Examples

height = 5.8temperature = 36.5

3. String (str)

Strings store text.

name = "Danesh"

Properties

Examples

city = "Chennai"

course = "Python"

4. Boolean (bool)

Booleans represent logical values.

is_active = True

Properties

Examples

is_logged_in = False

whatever we saw till now are primitive data types we will explore further on other data types in coming episodes

Checking Data Types

We can check the type using type().

Example

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image showing o/p on type() function

Comments in Python

Comments are notes written inside a program to explain the code. Python ignores comments during execution.

Comments help to:

Types of Comments in Python

Single-Line Comments

Single-line comments start with #.

Syntax

# This is a comment

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this image shows how the program ignores comment lines and prints output

Multi-Line Comments

Triple quotes are commonly used for multi-line comments.

Syntax

"""This is a multi-line comment"""

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example showing multi-line comments

Printing Variables

As seen Above variables can printed very easily in python

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image depicting printing variables

Printing Multiple Values

Multiple values can be printed using commas.

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Using Separator (sep)

The sep parameter changes the separator between values.

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Image showing usage of sep

Using End (end)

The end parameter changes the ending character.

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Overall printing functions are shown below

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Input in Python

Input means taking data from the user while the program is running. In Python, the input() function is used to receive values from the keyboard.

This makes programs interactive because the user can give different values every time the program runs.

Syntax:

input("Message")

The text inside quotes is shown to the user. Whatever the user types is returned by the input() function.

Basic Input Example

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Output

Enter your name: chipset

chipset

Explanation

Input with a Message

Usually, we display a message so the user understands what to enter.

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Important Point About input()

By default, Python stores all input values as strings (str).

Even if the user enters a number, Python treats it as text.

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image showing default input type

Why Type Conversion is Needed

Suppose we take two numbers as input:

a = input("Enter first number: ")

b = input("Enter second number: ")

print(a + b)

Output

1020

Explanation

Python joins the strings instead of adding them mathematically.

So, we need type conversion.

Integer Input using int()

The int() function converts input into an integer.

Image

image showing integer input

Explanation

Float Input using float()

The float() function converts input into decimal numbers.

Example

height = float(input("Enter height: "))

print(height)

Output

Enter height: 5.85.8

Taking Multiple Inputs

We can take multiple values from the user.

Example

name = input("Enter name: ")

age = int(input("Enter age: "))

print(name, age)

Output

Enter name: chipset

Enter age: 19

chipset 19

Real-Life Uses of Input

Input is used in:

Almost every interactive application uses input functions.

Homework

Try these programs on your own to improve your understanding of Python basics:

Conclusion

In this article, we learned the basic fundamentals of Python programming, including:

These concepts form the foundation of Python programming and are essential for Artificial Intelligence and Machine Learning development.

Keep practicing these basics regularly, because strong fundamentals make advanced programming much easier to learn.

Stay tuned for the next episode to explore more Python concepts and continue your journey into AI and Machine Learning.