This course covers designing and building a TensorFlow 2.x input data pipeline, building ML models with TensorFlow 2.x and Keras, improving the accuracy of ML models, writing ML models for scaled use and writing specialized ML models.
Introduction
Loading...
Kompetenzen, die Sie erwerben
Machine Learning, Python Programming, Build Input Data Pipeline, Tensorflow, keras
Bewertungen
4.4 (2,684 Bewertungen)
- 5 stars61,81 %
- 4 stars25,11 %
- 3 stars8,97 %
- 2 stars2,57 %
- 1 star1,52 %
DW
16. Okt. 2018
pretty good. some of the code in the last lab could be better explained. also please debug the cloud shell, as it does not always show the "web preview" button ;) otherwise, good job!
SS
5. Juni 2018
Nice introduce, might be more on introduce the model structure, because I still need to read additional notes to locate how to train my deep learning model online.
Aus der Unterrichtseinheit
Building Neural Networks with the TensorFlow and Keras API
In this module, we discuss activation functions and how they are needed to allow deep neural networks to capture nonlinearities of the data. We then provide an overview of Deep Neural Networks using the Keras Sequential and Functional APIs. Next we describe model subclassing, which offers greater flexibility in model building. The module ends with a lesson on regularization.
Unterrichtet von
Google Cloud Training
Durchsuchen Sie unseren Katalog
Melden Sie sich kostenlos an und erhalten Sie individuelle Empfehlungen, Aktualisierungen und Angebote.
Coursera Footer
© 2022 Coursera Inc. Alle Rechte vorbehalten.
