The beginning of Tang poetry has nothing to do with the text.
Li 11 lotus
Lu Zhaolin (632~ 695, born in Fanyang, Youzhou (Zhuozhou, Hebei). Since the name you Care son, and Yang Jiong, Wang Bo, Luobin king and known as the “early Tang Four heroes”, the world “Wang Yang Lu Luo”. Good at poetry parallel prose, especially good at seven words song line, artistic conception is clear.
Floating incense around the curved shore, round shadow covered pool.
Often fear autumn wind early, falling Jun do not know.
Why and how to learn data structures and algorithms?
Why learn?
Learning knowledge is for “use”, is to solve the problem in the actual work. Usually do not need to achieve their own, does not mean that they do not need to understand. Understanding data structures and algorithms, whether it’s reading the source code of the framework or understanding the design principles behind it, is very useful.
One: Simply write better code at work.
Second: algorithm is actually the idea and method to solve problems, a large number of applications in normal learning, work and life.
Third, the core of competition is actually people. Learning data structure and algorithm can effectively exercise brain logic and improve core competitiveness.
What are data structures and algorithms?
Broadly speaking, data structure refers to the storage structure of a group of data. An algorithm is a set of methods for manipulating data. Data structures and algorithms are complementary. Data structures serve algorithms, which operate on specific data structures.
For example, because of the random-access nature of arrays, the commonly used binary search algorithm group uses data to store data. If you choose a data structure like a linked list, binary lookup will not work because linked lists do not support random access.
A data organization is static; it is just a way of organizing data. Data structures that exist in isolation are useless if they don’t manipulate data and build algorithms on top of it.
First, let’s be clear: complexity analysis is very important in data structures and algorithms. Complexity analysis is a method to consider the efficiency and resource consumption of data structures and algorithms. It can be used to evaluate the applicability of a data structure and algorithm.
20 common data structures and algorithms:
10 data structures: array, linked list, stack, queue, hash table, binary tree, heap, hop table, graph, Trie tree.
10 common algorithms: recursion, sorting, binary search, search, hash algorithm, greedy algorithm, divide-and-conquer algorithm, backtracking algorithm, dynamic programming, string matching algorithm.
How to learn?
Practice while learning, moderate brush questions.
Ask questions and think.
Take more study notes.
Learning data structures and algorithms is a boring process, and self-motivation is important.
At the end of the recommendation algorithm visualization website, easy to understand and learn.
Data structure and algorithm visualization site
VisuAlgo：visualgo.net/zh
algorithm-visualizer：algorithm-visualizer.org/
www.cs.usfca.edu/~galles/vis…
Learning knowledge is a process of repeated iteration and continuous precipitation.