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Install the Scala plugin for Eclipse from Scala IDE. I use this update-site for scala 2.11 : http://download.scala-ide.org/sdk/lithium/e44/scala211/stable/site
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Install this eclipse plugin for maven / m2e : http://alchim31.free.fr/m2e-scala/update-site
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You can then import easily a Maven project from the provided pom.xml file
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Right-click on the project, Configure > Add Scala Nature
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/** | |
* Generate Case class from DataFrame.schema | |
* | |
* val df:DataFrame = ... | |
* | |
* val s2cc = new Schema2CaseClass | |
* import s2cc.implicit._ | |
* | |
* println(s2cc.schemaToCaseClass(df.schema, "MyClass")) | |
* |
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"""Short and sweet LSTM implementation in Tensorflow. | |
Motivation: | |
When Tensorflow was released, adding RNNs was a bit of a hack - it required | |
building separate graphs for every number of timesteps and was a bit obscure | |
to use. Since then TF devs added things like `dynamic_rnn`, `scan` and `map_fn`. | |
Currently the APIs are decent, but all the tutorials that I am aware of are not | |
making the best use of the new APIs. | |
Advantages of this implementation: |
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data { | |
int N; | |
int M; | |
real<lower=0> Y[N]; | |
} | |
parameters { | |
real<lower=0> mu; | |
real<lower=0> phi; | |
real<lower=1, upper=2> theta; |
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# Copyright 2015 Google Inc. All Rights Reserved. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, |
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""" | |
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
BSD License | |
""" | |
import numpy as np | |
# data I/O | |
data = open('input.txt', 'r').read() # should be simple plain text file | |
chars = list(set(data)) | |
data_size, vocab_size = len(data), len(chars) |
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---------------------------------------------------------------------- | |
-- CIFAR 8x8 | |
opt.scale = 8 | |
opt.geometry = {3, opt.scale, opt.scale} | |
local input_sz = opt.geometry[1] * opt.geometry[2] * opt.geometry[3] | |
local numhid = 600 | |
model_D = nn.Sequential() | |
model_D:add(nn.Reshape(input_sz)) | |
model_D:add(nn.Linear(input_sz, numhid)) | |
model_D:add(nn.ReLU()) |
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#!/usr/bin/python | |
# GoogleMapDownloader.py | |
# Created by Hayden Eskriett [http://eskriett.com] | |
# | |
# A script which when given a longitude, latitude and zoom level downloads a | |
# high resolution google map | |
# Find the associated blog post at: http://blog.eskriett.com/2013/07/19/downloading-google-maps/ | |
import urllib | |
import Image |
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