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Francois Vanderseypen Orbifold

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Happy. Thinking. Understanding.
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Orbifold / OptimalPortfolio.R
Created November 10, 2016 13:46
Computing the efficient frontier in R
library(stockPortfolio)
library(quadprog)
library(ggplot2)
stocks <- c("SPY", "EFA", "IWM", "VWO", "LQD", "HYG")
returns <- getReturns(stocks, freq = "week")
eff.frontier <- function (returns,
short = "no",
max.allocation = NULL,
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Orbifold / Chi2NoiseReduction.R
Created November 11, 2016 06:36
Noise reduction using chi2. A synthetic proof by example.
probabilityInsideCluster = 0.5
probabilityOutsideCluster = 0.2
probabilityNoise = 0.3
clusterBoundaries = c(10, 25, 56, 81, 151, 293)
clientTypeCount = c(0, 0, 0, 0)
library(dplyr)
library(rpart)
# this create a frame of clients
makeClientsFrame = function(attribCount = 1000,
clientCount = 1000,
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Orbifold / SMOTE.ipynb
Created November 12, 2016 15:44
Highlighting the usage of synthetic data (SMOTE) to imbalanced data.
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Orbifold / Forecasting.ipynb
Last active April 19, 2024 17:33
A tutorial notebook on forecasting time series with R.
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Orbifold / ZeppelinPlot.py
Created November 17, 2016 07:08
Zeppelin plotly example.
# if needed, install plotly via shell like so
%sh pip install plotly
#---
%pyspark
import plotly
import numpy as np
from plotly.graph_objs import Scatter, Layout
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Orbifold / KendoZeppelin.py
Created November 17, 2016 07:54
Using Kendo inside a Zeppelin section is simple.
%angular
<base href="http://demos.telerik.com/kendo-ui/gantt/index">
<style>html { font-size: 14px; font-family: Arial, Helvetica, sans-serif; }</style>
<title></title>
<link rel="stylesheet" href="http://kendo.cdn.telerik.com/2016.3.1028/styles/kendo.common-material.min.css" />
<link rel="stylesheet" href="http://kendo.cdn.telerik.com/2016.3.1028/styles/kendo.material.min.css" />
<link rel="stylesheet" href="http://kendo.cdn.telerik.com/2016.3.1028/styles/kendo.material.mobile.min.css" />
<script src="http://kendo.cdn.telerik.com/2016.3.1028/js/jquery.min.js"></script>
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Orbifold / Feedforward.ipynb
Created November 25, 2016 09:47
Feedforward examples using Keras.
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Orbifold / Gensim.py
Created December 12, 2016 06:52
Using Word2Vec experiment on the Bible.
from gensim.utils import simple_preprocess
tokenize = lambda x: simple_preprocess(x)
# tokenize("We can load the vocabulary from the JSON file, and generate a reverse mapping (from index to word, so that we can decode an encoded string if we want)?!")
import os
import json
import numpy as np
from gensim.models import Word2Vec
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Orbifold / LSTM MxNet.R
Created December 12, 2016 18:43
An LSTM neural network reproducing mini Shakespeare.
require(mxnet)
batch.size = 32
seq.len = 32
num.hidden = 16
num.embed = 16
num.lstm.layer = 1
num.round = 1
learning.rate= 0.1
wd=0.00001
clip_gradient=1
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Orbifold / Embedding and Tokenizer in Keras.ipynb
Created January 10, 2017 07:41
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