josete89

// Playground - noun: a place where people can play
public func id<A>(x : A) -> A {
    return x
}

public func error<A>(_ x : String) -> A {
    assert(false, x)
}

/// The Continuation Monad

josete89

var data = {"id":1,"orderName":"Order from spain","teamName":"Portland penguins","orderType":"lock","discount":5,"contactName":"John doe","contactPhonePrefix":"+32","contactPhoneNumber":"3423232","contactEmail":"jhon.doe@mycompany.com","contactAddress":"830 Southwest","dealerId":"123","dealerNote":"Lorem ipsum","createdAt":"2017-11-13T16:40:12.000Z","updatedAt":"2017-11-13T16:40:12.000Z","products":[{"id":5,"externalId":"C77124","createdAt":"2017-11-13T16:40:12.000Z","updatedAt":"2017-11-13T16:40:12.000Z","OrderProduct":{"createdAt":"2017-11-13T16:40:12.000Z","updatedAt":"2017-11-13T16:40:12.000Z","orderId":1,"productId":5},"selectedSizes":[{"id":1,"technicalSize":520,"quantity":5,"createdAt":"2017-11-13T16:40:12.000Z","updatedAt":"2017-11-13T16:40:12.000Z","ProductSelectedSize":{"createdAt":"2017-11-13T16:40:12.000Z","updatedAt":"2017-11-13T16:40:12.000Z","productId":5,"selectedSizeId":1}}]}]}
var transformation = {"id":"id","order_name":"orderName","team_name":"teamName","order_type":"orderType","discount":

josete89

 
    func resize(to: CGFloat) -> UIImage {
        
        let scale = to / self.size.width
        let newHeight = self.size.height * scale
        UIGraphicsBeginImageContext(CGSize(width: to, height: newHeight))
        self.draw(in: CGRect(x: 0, y: 0, width: to, height: newHeight))
        let newImage = UIGraphicsGetImageFromCurrentImageContext()
        UIGraphicsEndImageContext()
        

josete89

from keras.engine import Model
from keras.layers import GlobalAveragePooling2D, Dense
from keras.optimizers import SGD
from keras.preprocessing.image import ImageDataGenerator
from keras.applications import InceptionV3
from keras.applications.inception_v3 import preprocess_input
from coremltools.converters.keras import convert
from keras.models import load_model

train_data_dir = "./../data/train"

josete89

import * as tf from '@tensorflow/tfjs'
const app = requiere('express')()

import '@tensorflow/tfjs-node'
tf.setBackend('tensorflow')

app.get('/model',(req,res) => {
  const prediction = await model.predict(req['x']).data()
  res.send(prediction)
})

josete89

from keras import regularizers

model = models.Sequential()
model.add(layers.Dense(16, kernel_regularizer=regularizers.l2(0.001),
                       activation='relu', input_shape=(10000,)))
model.add(layers.Dense(16, kernel_regularizer=regularizers.l2(0.001),
                       activation='relu'))
model.add(layers.Dense(1, activation='sigmoid'))

josete89

model = models.Sequential()
model.add(layers.Dense(16, activation='relu', input_shape=(10000,)))
model.add(layers.Dropout(0.5))
model.add(layers.Dense(16, activation='relu'))
model.add(layers.Dropout(0.5))
model.add(layers.Dense(1, activation='sigmoid'))

josete89

from keras.models import Sequential
from keras import models

model = Sequential()
...
# serialize model
model.save('my_model.hd5')

# later...

josete89

from coremltools.converters.keras import convert
from keras.models import Sequential

model = Sequential()
...
# In case the model accept a image as input will be more
# easier for iOS code declare in that way.
coreml_model = convert(model, image_input_names="input1")
coreml_model.save('my_model.mlmodel')

josete89

class GetParam<A>{
    readonly _tag: 'GetParam' = 'GetParam';
    readonly _A!: A;
    readonly _URI!: RequestLifeCycleFURI;
    constructor(readonly url: string,readonly more: (param:either.Either<Error,string>)=> A){ }
}

class Validate<A> {
    readonly _tag: 'Validate' = 'Validate';