练习 3：特征提取和微调
在本练习中，您将对 Google 的 Inception v3 模型应用特征提取和微调技巧，以进一步提高练习 1 和练习 2 中的猫狗分类器的准确率：
机器学习实践：图像分类
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最后更新时间 (UTC)：2025-01-28。
[null,null,["最后更新时间 (UTC)：2025-01-28。"],[[["\u003cp\u003eThis exercise leverages Google's Inception v3 model through feature extraction and fine-tuning to enhance the accuracy of a cat-vs-dog image classifier.\u003c/p\u003e\n"],["\u003cp\u003eIt builds upon the previous exercises on image classification, refining the model for better performance.\u003c/p\u003e\n"],["\u003cp\u003eYou will practically implement these techniques using a provided Google Colab notebook.\u003c/p\u003e\n"]]],[],null,["# ML Practicum: Image Classification\n\n\u003cbr /\u003e\n\n### Exercise 3: Feature Extraction and Fine-Tuning\n\nIn this exercise, you'll use feature extraction and fine-tuning to\nleverage Google's Inception v3 model to achieve even better accuracy for the\ncat-vs.-dog classifier from Exercises [1](/machine-learning/practica/image-classification/exercise-1) and\n[2](/machine-learning/practica/image-classification/exercise-2): \n[Launch exercise](https://colab.research.google.com/github/google/eng-edu/blob/main/ml/pc/exercises/image_classification_part3.ipynb?utm_source=practicum-IC&utm_campaign=colab-external&utm_medium=referral&hl=en&utm_content=imageexercise3-colab)"]]