Deep Learning with PyTorch : Convolutional Neural Network

Coursera Project Network
학습자는 이 안내 프로젝트에서 다음을 수행하게 됩니다.

Create Convolutional Neural Network using PyTorch

Write training loop for classifying images

Create, train and evaluate CNN

Clock2 hours
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

In this two hour project-based course, you will get to know basic components to create convolutional neural network using pytorch through hands-on tasks. You will learn how to create, train and evaluate a convolutional neural network using pytorch. By the end of this project, you will be able to build and train a convolutional neural network on CIFAR-10 dataset. This guided project is for learners who want to use pytorch for building deep learning models. Learners who have basic understanding of convolutional neural network and want to apply using a deep learning framework like pytorch. This project provides learners with deep knowledge about the basics of pytorch and its main components. In order to be successful in this project, you should be familiar with python and neural networks.

개발할 기술

  • Convolutional Neural Network
  • Python Programming
  • Deep Learning
  • pytorch

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

  1. Load CIFAR-10 Dataset

  2. Plot examples from dataset

  3. Loading Dataset into Batches

  4. Create Convolutional Neural Network

  5. Train Convolutional Neural Network

  6. Evaluate the model

  7. Optional Task : Finding mean and std value for normalization

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

자주 묻는 질문

자주 묻는 질문

궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.