| Description |
1 online resource (1 streaming video file (1 hr., 42 min., 25 sec.)) : digital, sound, color |
| Performer |
Presenter, Marvin Bertin. |
| Note |
Title from title screen (viewed April 20, 2017). |
|
Date of publication from resource description page. |
| Summary |
"TensorFlow-Slim (TF-Slim) is a TensorFlow wrapper library that allows you to build and train complex TensorFlow models in an easy, intuitive way by eliminating the boilerplate code that plagues many deep learning algorithms. This course teaches you how to use TF-Slim and is intended for learners with some previous experience working with TensorFlow. To get the most out of this training, learners should be familiar with the core concepts of data science theory (train/test splits, overfitting and underfitting, bias-variance tradeoffs, etc.), and deep learning theory (backpropogation, weight parameter tensors, neural network layers, objective and loss functions, and optimization via stochastic descent)."--Resource description page. |
| Subject |
Machine learning.
|
|
Artificial intelligence.
|
|
Apprentissage automatique. |
|
Intelligence artificielle. |
|
artificial intelligence. |
|
Artificial intelligence. |
|
Machine learning. |
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