算法

算法课程将帮助您学习解题计算过程,并且在软件中实现计算过程。您将学习设计搜索、排序和优化等算法,并且使用算法解决实际问题。

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Deep Learning
deeplearning.ai
Deep Learning
專項課程
Natural Language Processing
deeplearning.ai
Natural Language Processing
專項課程
Reinforcement Learning
University of Alberta
Reinforcement Learning
專項課程
Algorithms
Stanford University
Algorithms
專項課程
AI Foundations for Everyone
IBM
AI Foundations for Everyone
專項課程
数据结构与算法
University of California San Diego
数据结构与算法
專項課程
Accelerated Computer Science Fundamentals
University of Illinois at Urbana-Champaign
Accelerated Computer Science Fundamentals
專項課程
Introduction to Programming in C
Duke University
Introduction to Programming in C
專項課程
Introduction to Discrete Mathematics for Computer Science
National Research University Higher School of Economics
Introduction to Discrete Mathematics for Computer Science
專項課程
Excel/VBA for Creative Problem Solving
University of Colorado Boulder
Excel/VBA for Creative Problem Solving
專項課程
Fundamentals of Computing
Rice University
Fundamentals of Computing
專項課程
Bioinformatics
University of California San Diego
Bioinformatics
專項課程
Algorithms for Battery Management Systems
University of Colorado System
Algorithms for Battery Management Systems
專項課程
Probabilistic Graphical Models
Stanford University
Probabilistic Graphical Models
專項課程
Machine Learning and Reinforcement Learning in Finance
New York University
Machine Learning and Reinforcement Learning in Finance
專項課程
程序设计与算法
Peking University
程序设计与算法
專項課程
Machine Learning: Algorithms in the Real World
Alberta Machine Intelligence Institute
Machine Learning: Algorithms in the Real World
專項課程
Mind and Machine
University of Colorado Boulder
Mind and Machine
專項課程
Fundamentos de IA para Todos
IBM
Fundamentos de IA para Todos
專項課程

    關於 算法 的常見問題

  • An algorithm is a step-by-step process used to solve a problem or reach a desired goal. It's a simple concept; you use your own algorithms for everyday tasks like deciding whether to drive or take the subway to work, or determining what you need from the grocery store. Software programs are an example of much more powerful algorithms, with computing resources used to execute multiple complex algorithms in parallel to solve much higher-level problems.

    As computers become more and more powerful, algorithms are helping them take on a life of their own - literally! Machine learning techniques rely on algorithms that learn and improve over time without need for a programmer's guidance. These techniques can be used to train algorithms for relatively simple tasks like image recognition or the automation and optimization of business workflows. And at their most complex, these algorithms are at the core of building the deep learning and artificial intelligence capabilities that many experts expect will transform our world even more than the advent of the internet!