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First, pick a network architecture; choose the layout of your neural network, including how many hidden units in each layer and how many layers in tot 阅读全文
posted @ 2020-09-16 03:32
Zhentiw
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section img { --aspect-ratio: calc( 4 / 3); --height: 30vmin; --width: calc(var(--height) * var(--aspect-ratio)); height: var(--height); width: var(-- 阅读全文
posted @ 2020-09-15 23:42
Zhentiw
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As you can see "Characters" take two params, page & filter. Here use two alias: allChars: characters fullNmae: name. Alias is also useful when you nee 阅读全文
posted @ 2020-09-15 23:32
Zhentiw
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Gradient checking will assure that our backpropagation works as intended. We can approximate the derivative of our cost function with: epsilon = 1e-4; 阅读全文
posted @ 2020-09-15 23:23
Zhentiw
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When consuming asynchronous selectors in Recoil, you're going to need to tell React what to render while the API is fetching its data. One way to solv 阅读全文
posted @ 2020-09-13 22:28
Zhentiw
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In this lesson, we add a Docker configuration to our project. In the Dockerfile we specify the different layers of our Docker image. We use a pretty s 阅读全文
posted @ 2020-09-13 22:19
Zhentiw
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Install: npm i --save joi Example: const schema = Joi.object({ username: Joi.string() .alphanum() .min(3) .max(30) .required(), password: Joi.string() 阅读全文
posted @ 2020-09-13 22:09
Zhentiw
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With neural networks, we are working with sets of matrices: In order to use optimizing functions such as "fminunc()", we will want to "unroll" all the 阅读全文
posted @ 2020-09-13 02:12
Zhentiw
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In this lesson, we use CSS pseudo-elements and the mix-blend-mode property to create a duotone effect for an image. We wrap the image in a container e 阅读全文
posted @ 2020-09-10 16:06
Zhentiw
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"Backpropagation" is neural-network terminology for minimizing our cost function, just like what we were doing with gradient descent in logistic and l 阅读全文
posted @ 2020-09-10 02:58
Zhentiw
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