daveliepmann

(ns jump-sugar-james.application
  (:require [incanter.core :as i]
            [incanter.stats :as incs]
            [incanter.charts :as incc]
            [clj-ml.clusterers :as mlc]
            [clj-ml.data :as mld]
            [clojure.string :as s]))

;;;; We'll need some functions from earlier.

daveliepmann

Implementing the k-means jump method: Part Two

After implementing Sugar & James' jump method and exploring its application to Fisher's iris data in Part One of this series, we're now ready to apply the jumps-in-distortions test to some other sample data sets. Pure Clojure source here.

Remember these functions from earlier? We'll be using them again.

(defn assoc-distortions
  "Given a number `transformation-power-y` and a seq of maps

kenfehling

#!/usr/bin/env bash
# For opening a file from the heads up display of Figwheel in IntelliJ IDEA
# Made for OS X but should work similarly on Linux with a different CMD variable
# Add this script to your path (ex. ~/bin) and use from
# :open-file-command in the :figwheel section of project.clj

INTELLIJ_VERSION=14  # Change for your (whole number) version of IntelliJ IDEA

CMD="/Applications/IntelliJ IDEA ${INTELLIJ_VERSION}.app/Contents/MacOS/idea"
"$CMD" "$PWD" --line $2 "$PWD/$1"

karpathy

"""
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)

ptaoussanis

;;
;; LATEST UPDATE: 25 July 2015
;;
;; ****************************************************************
;; ** NB false alarm! My original benchmarks showing large perf  **
;; ** improvements with tuples turned out to be noise,           **
;; ** unfortunately. Current (+more reliable) numbers seem[1] to **
;; ** show no consistent significant advantage using currently   **
;; ** available tuple implementations against real-world code.   **
;; **                                                            **

arnaudsj

"""
This is a batched LSTM forward and backward pass
"""
import numpy as np
import code

class LSTM:
  
  @staticmethod
  def init(input_size, hidden_size, fancy_forget_bias_init = 3):

karpathy

"""
This is a batched LSTM forward and backward pass
"""
import numpy as np
import code

class LSTM:
  
  @staticmethod
  def init(input_size, hidden_size, fancy_forget_bias_init = 3):

aarondunnington

local ENQUEUE_CAPACITY = 100

local function l_exists(rec, bin)
  if aerospike:exists(rec)
    and rec[bin] ~= nil
      and type(rec) == "userdata" then
    return true
  end
  return false
end

deanrad

So you want to build a service?

This checklist, Chris Brown > Jonathan Locker > Dean Radcliffe

Do we need to build it in house? (We ♥ not reinventing the wheel)

• Have we researched commercially available products?
• Are there any licensed tools that we can add to our service to save on development costs?

mrocklin

#!/usr/bin/env python

from sys import argv
from into import into, Iterator
from toolz import partition

literals = [True, False, None]

def parse(s):
    """ Parse strings to booleans, integers, or strings """