kernels

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Neural Networks 89 16 Neural Networks NEURAL NETWORKS Can do both classification & regression. [They tie together many ideas from the course: perceptrons, linear regression, logistic regression, ensembles of learners, and stochastic gradient descent. They also tie in the idea of lifting sample points to a higher- dimensional feature space, but with a new twist: neural nets can learn features themselves.] [I want to begin by reminding you of the story I told you at the beginning of the semester, about Frank Rosenblatt’s invention of…

related reading

• Neural networks and deep learningneuralnetworksanddeeplearning.com
• Zoom In: An Introduction to Circuitsdistill.pub
• Neural Networks, Manifolds, and Topology -- colah's blogcolah.github.io
• Notes for a talk on the history of neural networks – Yuxi on the Wiredyuxi.ml
• Neural networks and deep learningneuralnetworksanddeeplearning.com
• Neural networks and deep learningneuralnetworksanddeeplearning.com
• A Recipe for Training Neural Networkskarpathy.github.io
• nn-notes.pdfboris-hanin.github.io
• Neural networks and deep learningneuralnetworksanddeeplearning.com
• 6.pdfweb.stanford.edu
• Perceptron - Wikipediaen.wikipedia.org
• A Recipe for Training Neural Networkskarpathy.github.io