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Embarking on the road of programming means that you have chosen a life-long learning lifestyle. Every programmer has to practice eighteen martial arts, and mastering data structures and algorithms is like practicing nine suns. In other words, if you master the data structure and algorithm, your internal strength practice speed will have a qualitative leap.
Whether you are engaged in business development and want to evaluate code performance and resource consumption; or are engaged in architecture design and want to optimize design patterns; or want to quickly play with popular technologies, such as artificial intelligence and blockchain, you must first get the data structure And algorithm. Because, no matter how new technology changes, as long as you master these core "tactics" of computer science, you can see and dismantle and stay in an "invincible position."
So how can we truly master data structures and algorithms? Is it memorizing commonly used data structures and algorithms? Even so, in the face of the ever-changing real world, you are unlikely to copy an algorithm to solve the next problem you are about to encounter. Therefore, just like learning design patterns and architecture patterns, the key to learning data structures and algorithms is to master the ideas and essence of them, and learn to solve practical problems .
Today, I recommend a Chinese booklet on algorithms that was once popular on the entire network. It is said that many small partners have successfully mastered the core skills of algorithms based on this guide and successfully obtained offers from major manufacturers such as BATJ.
Let me first show you what is in it:
One-click triple + comment, and then add the assistant's VX (bjmsb10) to receive the "Algorithm Booklet Full Version" for free.
Chapter 0, Must-Read Series
- Framework thinking of learning algorithm and problem solving
- Dynamic programming problem solving routine framework
- Backtracking algorithm problem solving routine framework
- BFS algorithm problem solving routine framework
- I wrote a poem so that you can write a binary search with your eyes closed
- I wrote a poem, turning the sliding window algorithm algorithm into a silent question
- One way to eliminate LeetCode stock trading problem
- A way to kill LeetCode
- A way to eliminate nSum problem
- Classic dynamic planning: throwing eggs in high buildings
- Classic dynamic programming: subset knapsack problem
- Classic dynamic programming: complete knapsack problem
- Expression evaluation algorithm: implement calculator
Chapter One, Dynamic Programming Series
- Dynamic programming problem solving routine framework
- Dynamic planning answers
- Who is the father of dynamic programming and backtracking algorithms?
- Dynamic programming design: the longest increasing subsequence
- Dynamic programming design: the largest sub-array
- Classical dynamic programming: 0-1 knapsack problem
- Classic dynamic programming: subset knapsack problem
- Classic dynamic programming: complete knapsack problem
- Classic dynamic programming: edit distance
- Classic dynamic planning: throwing eggs in high buildings
- Classic dynamic planning: throwing eggs in high buildings (advanced)
- Classic Dynamic Planning: Poke the balloon
- Classical dynamic programming: the longest common subsequence
- Dynamic programming sub-sequence problem solving template
- The Game Problem of Dynamic Programming
- Regular expression of dynamic programming
- Dynamic programming four-key keyboard
- KMP character matching algorithm for dynamic programming
- The Interval Scheduling Problem of Greedy Algorithms
- LeetCode's stock trading issues disappear
- LeetCode House Robbery Problem
Chapter Two, Data Structure Series
- What books to read about data structures and algorithms
- The road to algorithm learning
- Detailed binary heap implementation priority queue
- Detailed LRU algorithm
- Collection of Binary Search Tree Operations
- How to calculate the number of nodes in a complete binary tree
- Special data structure: monotonic stack
- Special data structure: monotonic queue
- Design Twitter
- Recursively reverse part of a linked list
- Queue implementation stack|Stack implementation queue
Chapter Three, Algorithmic Thinking Series
- Guide to learning algorithms and brushing questions
- Backtracking algorithm problem solving routine framework
- Backtracking algorithm clique annihilation subset, permutation, and combination problems
- Best Practice of Backtracking Algorithm: Solving Sudoku
- Best practice of backtracking algorithm: parenthesis generation
- Detailed binary search
- Summary of double pointer skills
- Sliding window technique
- The core idea of the twoSum problem
- Commonly used bit operations
- Dismantling complex problems: implementation calculator
- Biscuits sort
- Prefixes and tricks
- String multiplication
- Detailed explanation and application of FloodFill algorithm
- Interval merging problem of interval scheduling
- Interval Intersection Problem of Interval Scheduling
- Envelope nesting problem
- Several counter-intuitive probability problems
Chapter Four, High Frequency Interview Series
- How to implement the LRU algorithm
- How to use BFS algorithm to kill all kinds of puzzles
- How to efficiently find prime numbers
- How to efficiently perform modular exponentiation
- How to calculate edit distance
- How to use binary search algorithm
- How to efficiently solve the problem of receiving rainwater
- How to remove duplicate elements of an ordered array
- How to find the longest palindrome substring
- How to use greedy thinking to play jumping games
- How to reverse a set of k lists
- How to determine the legality of parentheses
- How to find missing elements
- How to find missing and duplicate elements at the same time
- How to determine the palindrome linked list
- How to randomly sample elements in an infinite sequence
- How to schedule candidates' seats
- Detailed Union-Find algorithm
- Union-Find algorithm application
- Algorithmic problems that can be solved in one line of code
- Binary search for efficient decision subsequence
Chapter 5 Technical Article Series
- What are Linux processes, threads, and file descriptors
- What you must know about the Linux shell
- Practical tips for Linux shell
- Understand session and cookie in one article
- The past and present of encryption algorithms
- I summarized all the routines of Git with four fate
- Git/SQL/Regular Expression Online Practice Platform
At present, the above content has been packaged into a complete e-book. The specific method of obtaining it is as follows:
One-click triple + comment, and then add the assistant's VX (bjmsb10) to receive the "Algorithm Booklet Full Version" for free.
There are also basic algorithm tutorials and detailed video tutorials of algorithm interview real questions by Teacher Ma Binjun and Zuo Chengyun
