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See lecture notes for week 39. -For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well. -
- -For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text.
- -For more discussions of project 1, chapter 5 of Goodfellow et al is a good read, in particular sections 5.1-5.5 and 5.7-5.11.These sections summarize neatly what we have done till now and point to what is coming with respect to deep learning.
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See lecture notes for week 39. -For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well. -
- -For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text.
- -For more discussions of project 1, chapter 5 of Goodfellow et al is a good read, in particular sections 5.1-5.5 and 5.7-5.11.These sections summarize neatly what we have done till now and point to what is coming with respect to deep learning.
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See lecture notes for week 39. -For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well. -
- -For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text.
- -For more discussions of project 1, chapter 5 of Goodfellow et al is a good read, in particular sections 5.1-5.5 and 5.7-5.11.These sections summarize neatly what we have done till now and point to what is coming with respect to deep learning.
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