* normalize the dataRaw input * @param {*} dataRaw

* Encodes a string or array based on the USE * @param {*} textString * @param {*} callback

* returns the prediction as an array synchronously * @param {*} _inputs

* synchronous predict internal * @param {*} _input * @param {*} _cb

* Read in a csv file from a path to its location. * @param {string} path

* Read in a csv file from a path to its location. * @param {string} path

* Saves metadata of the data * @param {*} nameOrCb * @param {*} cb

* creates a scatterplot from 1 input variable and 1 output variable * @param {*} inputLabel * @param {*} outputLabel * @param {*} data

* Segments the image with personSegmentation, return result object * @param {HTMLImageElement | HTMLCanvasElement | object | function | number} i

* Segments the image with partSegmentation, return result object * @param {HTMLImageElement | HTMLCanvasElement | object | function | number} img

* train * @param {*} optionsOrCallback * @param {*} optionsOrWhileTraining * @param {*} callback

* Train the model * @param {*} _options

* Visualize the training of the neural net

* Traverse the tree and download all the content, * transforming into an object keyed by file/directory name * @param {*} projectFileTree

* Traverse the tree and format into parent child relation * @param {*} parentObject

* STEP 3.1: Recursively get the tree of files for each directory * @param parentObject - one sketch directory object

* STEP 3.2: Traverse the sketchtree for all of the sketches * @param {*} categoryExamples - all of the categories in an array