Coursera - Image Understanding with TensorFlow on GCP
English | Size: 491.78 MB
Category: Tutorial
This is the third course of the Advanced Machine Learning on GCP specialization. In this course,
We will take a look at different strategies for building an image classifier using convolutional neural networks. We'll improve the model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting our data. We will also look at practical issues that arise, for example, when you don't have enough data and how to incorporate the latest research findings into our models.
You will get hands-on practice building and optimizing your own image classification models on a variety of public datasets in the labs we'll work on together.
Prerequisites: Basic SQL, familiarity with Python and TensorFlow
Miscellaneous
Provider: Coursera
Title: Image Understanding with TensorFlow on GCP
Knowledge must be free. We are a 0day e-learning release group.
You can find us on Discord and pass some exams together. You will know when you found us.
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