A colorful, informative statusline for Claude Code CLI.
- Directory (blue) - Current working directory
- Node version (green ⬢) - Shows when package.json exists
| {"lastUpload":"2021-10-02T06:25:20.555Z","extensionVersion":"v3.4.3"} |
adb and you can find it when you run adb devicescordova run android --device, Now the app will run on your devicechrome://inspect/#devices on your Chrome browser, and select your app and click inspect**/node_modulesprettier --write "**/*.js" *Don't forget the quotes.| // Future versions of Hyper may add additional config options, | |
| // which will not automatically be merged into this file. | |
| // See https://hyper.is#cfg for all currently supported options. | |
| module.exports = { | |
| config: { | |
| // default font size in pixels for all tabs | |
| fontSize: 14, | |
| // font family with optional fallbacks |
This list is meant to be a both a quick guide and reference for further research into these topics. It's basically a summary of that comp sci course you never took or forgot about, so there's no way it can cover everything in depth. It also will be available as a gist on Github for everyone to edit and add to.
| function [J grad] = nnCostFunction(nn_params, ... | |
| input_layer_size, ... | |
| hidden_layer_size, ... | |
| num_labels, ... | |
| X, y, lambda) | |
| %NNCOSTFUNCTION Implements the neural network cost function for a two layer | |
| %neural network which performs classification | |
| % [J grad] = NNCOSTFUNCTON(nn_params, hidden_layer_size, num_labels, ... | |
| % X, y, lambda) computes the cost and gradient of the neural network. The | |
| % parameters for the neural network are "unrolled" into the vector |