Python: Basics

Variables

In programming, a variable is like a container that stores data values. Think of it as a labeled box, where the label is the variable name, and the content inside is the data value.

In Python, creating a variable is straightforward:

x = 10
name = "Alice"

Here, x is a variable storing the integer value 10, and name stores the string "Alice".

Data Types

Python has various data types, and it's essential to understand the most common ones:

Integers: Whole numbers, either positive or negative.
```
age = 25
```
Floats: Numbers with a decimal point.
```
height = 5.9
```
Strings: Sequence of characters, enclosed within single or double quotes.
```
greeting = "Hello, World!"
```
Booleans: Represents either True or False.
```
is_student = False
```

Casting

Sometimes, you might want to change the data type of a value. This process is called casting. Python provides built-in functions to perform casting:

int(): Converts a value to an integer.
float(): Converts a value to a float.
str(): Converts a value to a string.

For example:

x = 5.5
y = int(x)  # y will be 5

Output

Displaying output in Python is done using the print() function:

print("Hello, World!")

You can also combine strings and variables:

name = "Anna"
print("Hello, " + name + "!")

Math

Python offers a variety of mathematical operations that can be performed on numbers:

Addition (+): 5 + 3 will return 8.
Subtraction (-): 5 - 3 will return 2.
Multiplication (*): 5 * 3 will return 15.
Division (/): 5 / 3 will return approximately 1.6667.

For more advanced mathematical functions, Python has a built-in module called math:

import math
result = math.sqrt(25)  # returns 5.0

Random Values

Generating random numbers is crucial in many applications, including machine learning. The random module in Python provides functions to generate random values:

import random
random_number = random.randint(1, 10)  # generates a random integer between 1 and 10

Nan & Inf

In Python, NaN stands for "Not a Number" and represents undefined or unrepresentable values. Inf denotes infinity, a value that's larger than any number.

These values can be encountered in computations, especially in the context of data science and machine learning:

import numpy as np

# Creating NaN and Inf values
x = np.nan
y = np.inf

print(x)  # Outputs: nan
print(y)  # Outputs: inf

Conclusion

Mastering the basics of Python is the first step towards a successful journey in machine learning. With its intuitive syntax and robust features, Python offers a seamless experience for beginners and professionals alike. As you progress, you'll find Python's versatility and power indispensable in your machine learning projects. Dive in, explore, and let Python be your guide in the captivating world of machine learning.

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