Learning Algorithms

Hello, I'm glad you're interested in learning algorithms! I am a professor and you are my student whom I teach algorithms in accordance with the book "Growing the Algorithm". How can I help you? Of course, let me tell you more about the process of learning algorithms in accordance with the book "Groaming the Algorithm". Chapter 1 of the book is titled "Introduction to Algorithms" and covers pages 1 to 14. It provides a general introduction to algorithms and shows how they are used in real life, starting with the task of finding a specific element in a list. The chapter also explains basic concepts such as arrays, the execution time of algorithms, and the big "O" notation. To consolidate the knowledge from the chapter, I recommend doing the following exercises: Write a Python program that finds the smallest element in a list. Write a Python program that finds the sum of all elements in a list. Solve the problem of finding an element in a sorted array in Python. Solve the problem of finding an element in an unsorted array in Python. Cheat sheet for doing exercises: To find the smallest element in a list, you can use the min() method in Python. To find the sum of the elements in a list, you can use the sum() function in Python. To solve the problem of finding an element in a sorted array, you can use binary search. To solve the problem of finding an element in an unsorted array, you can use a simple iteration of elements in a loop. You can find many examples of solving similar problems in Python on Github, for example, in the "Python-Algorithms" repository (https://github.com/TheAlgorithms/Python). Of course, here is a list of the chapters of the book "Groaming the Algorithm": Introduction to Algorithms Selection sort recursion Quick sort Hash tables Width and Depth Dijkstra and the Counts Greedy Algorithms Dynamic programming K-nearest neighbors Block sort caching When requested by chapter number or topic, I can display information about the chapter content, explain basic concepts and algorithms, offer exercises to consolidate knowledge and provide links to Github repositories where you can find solutions to similar problems in the Python programming language. Глава 4 книги "Грокаем алгоритм" посвящена быстрой сортировке. В этой главе рассматриваются следующие темы: Реализация алгоритма быстрой сортировки на языке Python Описание алгоритма разбиения массива на подмассивы с использованием опорного элемента Рекурсивный вызов быстрой сортировки для подмассивов Анализ временной сложности алгоритма в среднем и в худшем случае Сравнение быстрой сортировки с другими алгоритмами сортировки Упражнения в конце главы включают: Реализация быстрой сортировки на другом языке программирования Анализ временной сложности сортировки в худшем случае для случая, когда выбирается крайний элемент в качестве опорного Реализация быстрой сортировки с использованием стека вместо рекурсии Решение задачи о нахождении k-го по величине элемента в массиве с использованием быстрой сортировки Шпаргалка для реализации алгоритма быстрой сортировки на языке Python: c Copy code def quicksort(array): if len(array) < 2: return array else: pivot = array[0] less = [i for i in array[1:] if i <= pivot] greater = [i for i in array[1:] if i > pivot] return quicksort(less) + [pivot] + quicksort(greater) Ссылки на репозитории на Github с решениями задач на Python, связанных с быстрой сортировкой: https://github.com/TheAlgorithms/Python/blob/master/sorts/quick_sort.py https://github.com/TheAlgorithms/Python/blob/master/searches/kth_largest_element_quickselect.py