mtambos

Andrea Frome, Greg S Corrado, Jon Shlens, Samy Bengio, Jeff Dean, Tomas Mikolov, and Others. Devise: A deep visual-semantic embedding model.

Lukasz Kaiser, Aidan N Gomez, Noam Shazeer, Ashish Vaswani, Niki Parmar, Llion Jones, and Jakob Uszkoreit. One Model To Learn Them All.

Ryan Kiros, Ruslan Salakhutdinov, and Richard S Zemel. Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models.

Nitish Srivastava and Ruslan R Salakhutdinov. Multimodal learning with deep boltzmann machines.

Mohammad Norouzi, Tomas Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg S Corrado, and Jeffrey Dean. Zero-shot learning by convex combination of semantic embeddings.

mtambos

# Copyright (c) 2017 Mario Tambos

# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:

# The above copyright notice and this permission notice shall be included in all

mtambos

mtambos

mtambos

import numpy as np


class RingBuffer(np.ndarray):
    'A multidimensional ring buffer.'
    
    def __new__(cls, input_array):
        obj = np.asarray(input_array).view(cls)
        return obj

mtambos

timestamp,V5
datetime,float
T,
2014-10-07 00:00:00,4.8
2014-10-07 00:00:00.020000,4.79
2014-10-07 00:00:00.040000,4.8100000000000005
2014-10-07 00:00:00.060000,4.838
2014-10-07 00:00:00.080000,4.8839999999999995
2014-10-07 00:00:00.100000,4.956
2014-10-07 00:00:00.120000,5.026000000000001

mtambos

SWARM_DESCRIPTION = {
    'includedFields': [
        {
            'fieldName': 'timestamp',
            'fieldType': 'datetime',
        },
        {
            'fieldName': 'V5',
            'fieldType': 'float',
        },

mtambos

MODEL_PARAMS = (
{   'aggregationInfo': {   'days': 0,
                           'fields': [],
                           'hours': 0,
                           'microseconds': 0,
                           'milliseconds': 0,
                           'minutes': 0,
                           'months': 0,
                           'seconds': 0,
                           'weeks': 0,