Hands-On TensorBoard for PyTorch Developers:
Build better PyTorch models with TensorBoard visualization About This Video Learn everything you need to know to start using TensorBoard in PyTorch with practical examples in Machine Learning, Image Classification, and Natural Language Processing (NLP) Launch TensorBoard from any developer environme...
Gespeichert in:
| Körperschaften: | , |
|---|---|
| Format: | Elektronisch Video |
| Sprache: | Englisch |
| Veröffentlicht: |
[Erscheinungsort nicht ermittelbar]
Packt Publishing
2020
|
| Ausgabe: | 1st edition. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781838983604/?ar |
| Zusammenfassung: | Build better PyTorch models with TensorBoard visualization About This Video Learn everything you need to know to start using TensorBoard in PyTorch with practical examples in Machine Learning, Image Classification, and Natural Language Processing (NLP) Launch TensorBoard from any developer environment, including Jupyter notebooks and Google Colab Visualize and optimize your PyTorch models using techniques such as model graphs, training curves, image data, text embeddings, and many more In Detail TensorBoard is a visualization library for TensorFlow that plots training runs, tensors, and graphs. TensorBoard has been natively supported since the PyTorch 1.1 release. In this course, you will learn how to perform Machine Learning visualization in PyTorch via TensorBoard. This course is full of practical, hands-on examples. You will begin with a quick introduction to TensorBoard and how it is used to plot your PyTorch training models. You will learn how to write TensorBoard events and run TensorBoard with PyTorch to obtain visualizations of the training progress of a neural network. You will visualize scalar values, images, text and more, and save them as events. You will log events in PyTorch-for example, scalar, image, audio, histogram, text, embedding, and back-propagation. By the end of the course, you will be confident enough to use TensorBoard visualizations in PyTorch for your real-world projects. |
| Beschreibung: | Online resource; Title from title screen (viewed March 31, 2020) |
| Umfang: | 1 Online-Ressource (1 video file, approximately 2 hr., 13 min.) |
| Format: | Mode of access: World Wide Web. |
| ISBN: | 9781838983604 |
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| spelling | Hands-On TensorBoard for PyTorch Developers Papa, Joe 1st edition. [Erscheinungsort nicht ermittelbar] Packt Publishing 2020 Boston, MA Safari. 1 Online-Ressource (1 video file, approximately 2 hr., 13 min.) zweidimensionales bewegtes Bild tdi rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Online resource; Title from title screen (viewed March 31, 2020) Build better PyTorch models with TensorBoard visualization About This Video Learn everything you need to know to start using TensorBoard in PyTorch with practical examples in Machine Learning, Image Classification, and Natural Language Processing (NLP) Launch TensorBoard from any developer environment, including Jupyter notebooks and Google Colab Visualize and optimize your PyTorch models using techniques such as model graphs, training curves, image data, text embeddings, and many more In Detail TensorBoard is a visualization library for TensorFlow that plots training runs, tensors, and graphs. TensorBoard has been natively supported since the PyTorch 1.1 release. In this course, you will learn how to perform Machine Learning visualization in PyTorch via TensorBoard. This course is full of practical, hands-on examples. You will begin with a quick introduction to TensorBoard and how it is used to plot your PyTorch training models. You will learn how to write TensorBoard events and run TensorBoard with PyTorch to obtain visualizations of the training progress of a neural network. You will visualize scalar values, images, text and more, and save them as events. You will log events in PyTorch-for example, scalar, image, audio, histogram, text, embedding, and back-propagation. By the end of the course, you will be confident enough to use TensorBoard visualizations in PyTorch for your real-world projects. Mode of access: World Wide Web. Internet videos Streaming video Vidéos sur Internet Vidéo en continu streaming video Electronic videos Papa Joe MitwirkendeR ctb Safari, an O'Reilly Media Company. MitwirkendeR ctb 1838983600 Erscheint auch als Druck-Ausgabe 1838983600 |
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| title | Hands-On TensorBoard for PyTorch Developers |
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| title_full_unstemmed | Hands-On TensorBoard for PyTorch Developers Papa, Joe |
| title_short | Hands-On TensorBoard for PyTorch Developers |
| title_sort | hands on tensorboard for pytorch developers |
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