알고리즘

알고리즘 강좌는 문제 해결을 위한 과정을 명확하게 하고 소프트웨어 내의 처리를 효과적이게 구현하는 능력을 발달시켜줍니다. 검색, 정렬 및 최적화를 위한 알고리즘 디자인을 배우고 연습 질문에 답하는데 이를 적용할 수 있습니다.

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필터링 기준:
183 결과
정렬 기준:
Neural Networks and Deep Learning

Neural Networks and Deep Learning

deeplearning.ai
강좌
5점 만점에 4.9점을 받았습니다. 91523 리뷰
Natural Language Processing with Classification and Vector Spaces

Natural Language Processing with Classification and Vector Spaces

deeplearning.ai
강좌
5점 만점에 4.6점을 받았습니다. 941 리뷰
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

deeplearning.ai
강좌
5점 만점에 4.9점을 받았습니다. 52822 리뷰
Computational Thinking for Problem Solving

Computational Thinking for Problem Solving

University of Pennsylvania
강좌
5점 만점에 4.7점을 받았습니다. 718 리뷰
Convolutional Neural Networks

Convolutional Neural Networks

deeplearning.ai
강좌
5점 만점에 4.9점을 받았습니다. 34844 리뷰
Natural Language Processing with Probabilistic Models

Natural Language Processing with Probabilistic Models

deeplearning.ai
강좌
5점 만점에 4.8점을 받았습니다. 277 리뷰
Introduction to Artificial Intelligence (AI)

Introduction to Artificial Intelligence (AI)

IBM
강좌
5점 만점에 4.7점을 받았습니다. 4649 리뷰
Sequence Models

Sequence Models

deeplearning.ai
강좌
5점 만점에 4.8점을 받았습니다. 23751 리뷰
Divide and Conquer, Sorting and Searching, and Randomized Algorithms

Divide and Conquer, Sorting and Searching, and Randomized Algorithms

Stanford University
강좌
5점 만점에 4.8점을 받았습니다. 4069 리뷰
Build a Modern Computer from First Principles: From Nand to Tetris (Project-Centered Course)

Build a Modern Computer from First Principles: From Nand to Tetris (Project-Centered Course)

Hebrew University of Jerusalem
강좌
5점 만점에 4.9점을 받았습니다. 2280 리뷰
Machine Learning with Python

Machine Learning with Python

IBM
강좌
5점 만점에 4.7점을 받았습니다. 9415 리뷰
Fundamentals of Reinforcement Learning

Fundamentals of Reinforcement Learning

University of Alberta
강좌
5점 만점에 4.8점을 받았습니다. 1354 리뷰
Getting Started with SAS Programming

Getting Started with SAS Programming

SAS
강좌
5점 만점에 4.9점을 받았습니다. 1190 리뷰
Natural Language Processing with Sequence Models

Natural Language Processing with Sequence Models

deeplearning.ai
강좌
5점 만점에 4.4점을 받았습니다. 61 리뷰
Introducción a la programación en Python I: Aprendiendo a programar con Python

Introducción a la programación en Python I: Aprendiendo a programar con Python

Pontificia Universidad Católica de Chile
강좌
5점 만점에 4.4점을 받았습니다. 1721 리뷰
Algorithmic Toolbox

Algorithmic Toolbox

University of California San Diego
강좌
5점 만점에 4.6점을 받았습니다. 8615 리뷰

    알고리즘에 대한 자주 묻는 질문

  • 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!