Image Understanding with TensorFlow on GCP

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.
Course info
Level
Advanced
Updated
Sep 17, 2019
Duration
4h 20m
Table of contents
Welcome to Image Understanding with TensorFlow on GCP
Linear and DNN Models
Convolutional Neural Networks (CNNs)
Dealing with Data Scarcity
Going Deeper Faster
Pre-built ML Models for Image Classification
Summary
Description
Course info
Level
Advanced
Updated
Sep 17, 2019
Duration
4h 20m
Description

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.

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About the author

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