Fine-tuning Convolutional Networks to Classify Dog Breeds

提供方
Coursera Project Network
在此指導項目中,您將:

Create TensorFlow pipelines

Interpret model performance and ask poignant questions about the data

Fine-tune large-scale model on our niche dataset

Clock2 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

In this 2 hour-long project, you will learn how to approach an image classification task using TensorFlow. You will learn how to effectively preprocess your data to improve model generalizability, as well as build a performant modeling pipeline. Furthermore, you will learn how to accurately evaluate model performance using a confusion matrix; how to interpret results; and how to ask poignant questions about your dataset. Finally, you will fine-tune an existing, state-of-the-art-ready model to improve performance further. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

您要培養的技能

  • Convolutional Neural Network
  • Machine Learning
  • Image Preprocessing
  • Tensorflow
  • Fine-tuning

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Introduction to the project and exploratory data analysis

  2. Convolutional Neural Network quickstart guide

  3. Dataset (image) preprocessing

  4. Building a performant model pipeline

  5. Designing and evaluating a basic Convolutional Neural Network

  6. Fine-tuning a large-scale model for our usecase

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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