In Python, regular named functions and lambda functions are two important ways of defining reusable operations. Both can be used to perform calculations, process data, and pass behavior as an argument to another function. However, they differ in syntax, structure, readability, reusability, and typical applications. In Data Structures and Algorithms, these differences are particularly useful when processing collections such as lists, tuples, sets, and dictionaries. A regular named function is defined using the `def` keyword and is given an explicit name. It can contain multiple statements, conditional logic, loops, exception handling, documentation strings, and return statements. Because it has a name, it can be called repeatedly from different parts of a program. For example, a function that determines whether a student's marks are greater than 60 can be written as: ```python def is_eligible(marks): return marks >= 60 ``` The function can then be called using `is_eligible(75)`. Named functions are suitable when the operation is complex, needs to be reused many times, or requires clear documentation. A lambda function, on the other hand, is an anonymous function created using the `lambda` keyword. It generally contains a single expression and automatically returns the value of that expression. Its basic form is: ```python lambda arguments: expression ``` For example: ```python is_eligible = lambda marks: marks >= 60 ``` The lambda expression performs the same operation as the named function but in a shorter form. Lambda functions are particularly useful when a small function is needed temporarily and does not require a separate function definition. The major difference between the two is syntax and complexity. A named function uses `def`, has a function name, and can contain several statements. A lambda function is usually unnamed and is restricted to a single expression. For example: ```python def square(x): return x * x ``` can be represented as: ```python lambda x: x * x ``` The named version is generally more readable when the function is important or reused frequently, whereas the lambda version is convenient when the operation is simple and used locally. Another important difference is the way these functions are commonly used with higher-order functions. A higher-order function is a function that accepts another function as an argument, returns a function, or performs both operations. Higher-order functions are a fundamental concept in functional programming and are very useful in data structures and algorithms for filtering, mapping, and transforming collections. Python provides several built-in higher-order functions, including `filter()`, `map()`, and `sorted()`. The