jkleint

#!/usr/bin/env python
"""
Example of using Keras to implement a 1D convolutional neural network (CNN) for timeseries prediction.
"""

from __future__ import print_function, division

import numpy as np
from keras.layers import Convolution1D, Dense, MaxPooling1D, Flatten
from keras.models import Sequential

mjdietzx

"""
Clean and simple Keras implementation of network architectures described in:
    - (ResNet-50) [Deep Residual Learning for Image Recognition](https://arxiv.org/pdf/1512.03385.pdf).
    - (ResNeXt-50 32x4d) [Aggregated Residual Transformations for Deep Neural Networks](https://arxiv.org/pdf/1611.05431.pdf).
    
Python 3.
"""

from keras import layers
from keras import models

makuchaku

import json
from datetime import datetime, timedelta


# Copies logic from https://www.quantconnect.com/tutorials/strategy-library/fundamental-factor-long-short-strategy
# Algo storing - https://www.quantconnect.com/docs/algorithm-framework/algorithm-scoring
class ChartMillBackTester(QCAlgorithm):

    def Initialize(self):
        self.SetCash(1000*100) # Are't we rich? :D