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Eric Zelikman 2020-12-10 12:41:00 -05:00
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C3W1_Generative_Teaching_Networks_(Optional).ipynb
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"\n", "\n",
"4. **Neural Architecture Search.** But wait, there's still more! The generator doesn't just guide student training, it also can help determine the optimal student architecture (i.e. which layers, network depth). This concept of learning the best architecture is called Neural Architecture Search, or NAS. Pretty convenient, huh!\n", "4. **Neural Architecture Search.** But wait, there's still more! The generator doesn't just guide student training, it also can help determine the optimal student architecture (i.e. which layers, network depth). This concept of learning the best architecture is called Neural Architecture Search, or NAS. Pretty convenient, huh!\n",
"\n", "\n",
"![Figure 1a from the paper](https://drive.google.com/uc?id=1y1eEkAkyDRHjX6NzAZkjsVZ8m6HEL557)\n", "![Figure 1a from the paper](https://github.com/https-deeplearning-ai/GANs-Public/blob/master/gtn_fig1.png?raw=true)\n",
"*Figure 1(a) from the [GTN paper](https://arxiv.org/pdf/1912.07768.pdf), providing an overview of the method*\n", "*Figure 1(a) from the [GTN paper](https://arxiv.org/pdf/1912.07768.pdf), providing an overview of the method*\n",
"\n", "\n",
"### Learning Objectives\n", "### Learning Objectives\n",