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Description of  Introduction to Algorithms and Data Structures: A solid foundation for the real world of machine learning and data analytics

1222093170 pdf,epub Learning algorithms and data structures from this book will help you become a better programmer. Algorithms and data structures will make you think more logically. Furthermore, they can help you design better systems for storing and processing data. They also serve as a tool for optimization and problem-solving. As a result, the concepts of algorithms and data structures are very valuable in any field. For example, you can use them when building a web app or writing software for other devices. You can apply them to machine learning and data analytics, which are two hot areas right now. If you are a hacker, algorithms and data structures in Python are also important for you everywhere. Now, whatever your preferred learning style, I've got you covered. If you're a visual learner, you'll love my clear diagrams and illustrations throughout this book. If you're a practical learner, you'll love my hands-on lessons so that you can get practical with algorithms and data structures and learn in a hands-on way. Course Structure There are three volumes in this course. This is volume one. In this volume, you'll take a deep dive into the world of algorithms. With increasing frequency, algorithms are starting to shape our lives in many ways - from the products recommended to us, to the friends we interact with on social media, to even important social issues like policing, privacy and healthcare. So, the first part of this course covers what algorithms are, how they work, and where they can be found (real life applications). In the second volume, you'll work through an introduction to data structures. You're going to learn about two introductory data structures - arrays and linked lists. You'll look at common operations and how the runtimes of these operations affect our everyday code. In the third volume, you're going to bring your knowledge of algorithms and data structures together to solve the problem of sorting data using the Merge Sort algorithm. In this volume, we will look at algorithms in two categories: sorting and searching. You'll implement well-known sorting algorithms like Selection Sort, Quicksort, and Merge Sort. You'll also learn basic search algorithms like Sequential Search and Binary Search. At the end of many sections of this book, short practice exercises are provided to test your understanding of the topic discussed. Answers are also provided so you can check how well you have performed in each section. At the end of the book, assessment tests are provided. You will also find links to download more helpful resources such as codes and screenshots used in this book, and more practice exercises. You can use them for quick references and revision as well. My support link is also provided so you to contact me any time if you have questions or need further help. By the end of this course, you will understand what algorithms and data structures are, how they are measured and evaluated, and how they are used to solve real-life problems. So, everything you need is right here in this course. I really hope you’ll enjoy it. Are you ready? Let's dive in! Table of Contents: 0. What You Will Learn & How to Get Help 0.1. Benefits of learning about algorithms and data structures 0.2. Course Structure 1. Introduction to Algorithms 1.1. Playing a Counting Game 1.1.1. What is an Algorithm? 1.1.2. Guess the Number Game 1.1.3. Algorithm Guidelines 1.1.4. Practice Exercise 1 1.1.5. Answers to Practice Exercise 1 1.1.6. Evaluating Linear Search 1.1.7. Evaluating Binary Search 1.1.8. Practice Exercise 2 1.1.9. Answers to Practice Exercise 2 1.2. Time Complexity 1.2.1. Efficiency of an Algorithm 1.2.2. The Big O 1.2.3. Constant and Logarithmic Time 1.2.4. Linear & Quadratic Time 1.2.5. Cubic Runtime 1.2.6. Quasilinear Runtime 1.2.7. Polynomial Runtimes 1.2.8. Exponential Runtimes 1.2.9. How to Determine the Complexity of an Algorithm 1.2.10. Practice Exercise 3 1.2.11. Answers to Practice Exercise 3 1.3. Algorithms in Code 1.3.1. Linear Search in Code 1.3.2. Binary Search in Code 1.3.3. Recursive Binary Search in Code 1.3.4. Practice Exercise 4 1.3.5. Answers to Practice Exercise 4 1.4. Recursion and Space Complexity 1.4.1. Recursive Functions 1.4.2. Space Complexity 1.4.3. A Recap of What You Learned 1.4.4. Practice Exercise 5 1.4.5. Answers to Practice Exercise 5 1.5. Download Training Resources & Get Further Help Hours to read: 1 - 2 Total words: 23k