Grokking Algorithms: A Comprehensive Beginnerís Guide to Learn the Realms of Grokking Algorithms from A-Z

✍ Scribed by Eric Schmidt

• Tongue: English
• Leaves: 185
• Category: Library

✦ Synopsis

Discover the realms of Grokking algorithms

Do you think algorithms are complicated?
Does the mere thought of them make you break into a sweat and shake with anxiety?
Do you even know what they are?

You are not alone if you can answer 'yes' to any of the first three questions. Many would-be developers feel they have to understand algorithms inside out even to be considered real developers. I'm here to tell you that, while you need to understand them, learning algorithms is not as tough as you thought.

Data structures and algorithms are two of the biggest bugbears for most software developers. Developers who were educated traditionally likely learned about them in a couple of classes, while self-taught developers probably won't ever come across them in their learning. This is why they feel real anxiety when they come across them.

This book will remove all that anxiety and uncertainty and will cover the following subjects in an easy-to-understand manner:
• Algorithm strategies
• Algorithmic patterns
• The divide and conquer strategy
• Linked lists
• Data structures
• Stacks and queues
• Iteration and recursion
• Greedy algorithms
• Dijkstra's shortest path algorithm
• Random forests
• Sorting algorithms
• Hash tables and hashmaps

Throughout the book, you will see some code examples and plenty of real-world examples to help you learn these algorithms easier.

Don't waste any more time struggling through heavy mathematical and scientific journals – scroll up, click the “Add to Cart” button now, and set off on one of the easiest computer science journeys you will ever make.

✦ Table of Contents

Introduction
Chapter 1: Let’s Start with Strategy
Code It
Chapter 2: Looking for Patterns
Multiple Pointers
Divide and Conquer
O(1) Lookup: Object/Dictionary/Hash
Chapter 3: Divide and Conquer
Divide and Conquer Algorithm:
DAC vs. DP
Chapter 4: All about Data Structures
Arrays
Linked Lists
Stacks
Queues
Hash Tables
Trees
Heaps
Graphs
Chapter 5: How Linked Lists Work
Navigation
Other Uses
Chapter 6: Stacks and Queues
What Is a Stack?
Representation of Stacks
What Is a Queue?
Representation of Queues
Chapter 7: Recursion and Iteration
Recursion and Iteration: A Simple Example
Chapter 8: Let’s Get Greedy
What Is a Greedy Algorithm?
Creating a Greedy Algorithm
Chapter 9: Dijkstra’s Algorithm
Brief Introduction to Graphs
Introducing Dijkstra’s Algorithm
Example of Dijkstra's Algorithm
Chapter 10: Getting Lost in Random Forests
An Introduction to Random Forests
Random Forests vs. Decision Trees
Important Random Forest Hyperparameters
Advantages and Disadvantages
Chapter 11: The Best Sorting Algorithms
Classification of a Sorting Algorithm
Popular Sorting Algorithms
Chapter 12: What Are Hash Tables and HashMaps?
How Hash Tables Work
Basic Hash Table Examples
Hash Table Use Cases
FAQ
Bonus Chapter: A Simple Look at Big O Notation
Conclusion
References