Book Image

Introduction to Algorithms

By : Cuantum Technologies LLC
Book Image

Introduction to Algorithms

By: Cuantum Technologies LLC

Overview of this book

Begin your journey into the fascinating world of algorithms with this comprehensive course. Starting with an introduction to the basics, you will learn about pseudocode and flowcharts, the fundamental tools for representing algorithms. As you progress, you'll delve into the efficiency of algorithms, understanding how to evaluate and optimize them for better performance. The course will also cover various basic algorithm types, providing a solid foundation for further exploration. You will explore specific categories of algorithms, including search and sort algorithms, which are crucial for managing and retrieving data efficiently. You will also learn about graph algorithms, which are essential for solving problems related to networks and relationships. Additionally, the course will introduce you to the data structures commonly used in algorithms. Towards the end, the focus shifts to algorithm design techniques and their real-world applications. You will discover various strategies for creating efficient and effective algorithms and see how these techniques are applied in real-world scenarios. By the end of the course, you will have a thorough understanding of algorithmic principles and be equipped with the skills to apply them in your technical career.
Table of Contents (14 chapters)
11
Conclusion
12
Where to continue?
13
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5.4 Practice Problems

Problem 1: Linear Search

Write a Python function to implement a linear search algorithm. The function should take a list and the target value as parameters and return the index of the target value if it is in the list, otherwise return -1.

Solution:

Problem 2: Binary Search

Implement a Python function for a binary search. The function should take a sorted list and the target value as parameters. If the target value is in the list, return its index. Otherwise, return -1.

Solution:

Problem 3: Hashing

Suppose you have implemented a hash table with chaining to handle collisions. Now, you are given the keys: 10, 22, 31, 4, 15, 28, 17, 88, 59. Write a Python function to build the hash table using the hash function key mod 10.

Solution:

Problem 4: Binary Search vs Linear Search

Given a list of 1000 elements, at what point (number of elements) does it become faster to use a binary search rather than a linear search? Explain your reasoning.

These problems...