Location:Training / Machine Learning/Algorithm / Detailed explanation of algorithms: Stanford University’s classic video course / Makespan Minimization Part 1

The first volume of the four-part Detailed Explanation of Algorithms explains the basics of algorithms in detail and shows the essence of algorithms. It integrates many years of teaching experience of Stanford University professors and explains the profound things in a simple and easy-to-understand way.

Algorithms are the core and soul of computer science. Algorithms have a wide range of applications and are required for the implementation of network routing, computational genomics, public key cryptography and database systems. Studying algorithms can help us become better programmers, enable us to think more carefully, and successfully cope with technical interviews on various occasions.

This is a very easy-to-use introductory book on algorithms. It can be used as a learning book for programmers, and is also suitable for readers who want to learn algorithms and improve their algorithmic thinking skills.

This book mainly includes the following contents:
asymptotic analysis;
Big O notation;
master method;
fast divide and conquer algorithm;
randomization algorithm;
sorting algorithm;

Choose an algorithm.

Algorithms are the core and soul of computer science. Algorithms have a wide range of applications and are required for the implementation of network routing, computational genomics, public key cryptography and database systems. Studying algorithms can help us become better programmers, enable us to think more carefully, and successfully cope with technical interviews on various occasions.
This is a very easy-to-use introductory book on algorithms. It can be used as a learning book for programmers, and is also suitable for readers who want to learn algorithms and improve their algorithmic thinking skills.
This book mainly includes the following contents:
graph search and application;
hash table;
shortest path algorithm;
Bloom filter;
randomization algorithm;
heap;
search tree.