Tensorflow, Tensorflow, What is it that you see?
summary
Covers hands‑on specifics: Tensorflow runs on the GPU and TF Learn plus Jupyter Notebooks let code like model = fully_connected(...); fit(...) train a MNIST digit recognizer with TF Learn (10 outputs, batch size and epochs matter). Shows convolutional layers, pooling, 1x1 convs, LSTMs for sequence memory, and regularization tricks — dropout drops ~50% during training — and demos that worked: GANs that generate plausible bird images and face upscalers (Let’s Enhance) that sometimes produce convincing 4k detail.
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chapters (15)
- 0:00Intro
- 0:50What is deep learning
- 2:52Neural networks
- 4:53Logistic regression
- 12:19Deep learning
- 14:27Tensorflow Learn
- 21:14Overfitting
- 24:33Convolutional
- 31:07Recurrent
- 35:47Script Generation
- 36:21Translation
- 37:45generative adversarial networks
- 40:50face generation
- 42:26implications
- 43:24Resources
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