Mahdi Dibaiee
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728df02fbd
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feat(rnn): recurrent neural networks, experimental
WIP: runs out of memory quickly
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2016-10-25 20:23:55 +03:30 |
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Mahdi Dibaiee
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44f2ae372a
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chore(README): unnecessary space
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2016-10-17 01:59:48 +03:30 |
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Mahdi Dibaiee
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ace9b7f5f9
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chore(README): import statement
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2016-10-17 01:57:46 +03:30 |
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Mahdi Dibaiee
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ed6d2b3021
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feat(Numeric): move all modules to Numeric
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2016-10-17 01:54:35 +03:30 |
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Mahdi Dibaiee
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506b180498
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chore: package desc
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2016-10-16 13:11:27 +03:30 |
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Mahdi Dibaiee
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6da6e4fd09
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feat(pca): implement PCA and visualize data using it
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2016-10-11 16:28:09 +03:30 |
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Mahdi Dibaiee
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7f90afba7f
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chore(readme): time is relative to the machine
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2016-10-08 19:57:00 +03:30 |
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Mahdi Dibaiee
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016ebcaa93
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chore(README): notmnist-relu
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2016-10-03 19:22:55 +03:30 |
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Mahdi Dibaiee
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56fded810a
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chore(readme): word2vec chart explained
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2016-10-01 12:32:08 +03:30 |
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Mahdi Dibaiee
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85971bc84d
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feat(w2v): draw text charts for words
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2016-10-01 12:24:36 +03:30 |
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Mahdi Dibaiee
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d9d24f69a6
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feat(blogs-corpus): new corpus for word2vec
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2016-09-19 16:00:45 +04:30 |
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Mahdi Dibaiee
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f16cc26798
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perf(word2vec): better word2vec
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2016-09-16 18:46:21 +04:30 |
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Mahdi Dibaiee
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313e120f25
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crossEntropy chart for now
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2016-09-16 14:36:42 +04:30 |
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Mahdi Dibaiee
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6def5f6197
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draw chart using simple options
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2016-09-16 14:16:14 +04:30 |
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Mahdi Dibaiee
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0d43814448
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fix(word2vec): simple example of word2vec
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2016-09-16 14:03:15 +04:30 |
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Mahdi Dibaiee
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d4ac90bbd5
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rm(sin): remove sin example
fix(ignoreBiases): was ignoring nodes, lol
fix(w2v): better logging and implementation
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2016-09-16 13:31:23 +04:30 |
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Mahdi Dibaiee
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c0083f5c05
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fix(notmnist): notmnist sigmoid chart with 10 epochs
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2016-09-13 10:04:30 +04:30 |
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Mahdi Dibaiee
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6b9cb1fa3e
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relu: run notmnist using relu activation and draw the chart
[wip] word2vec: work in progress implementation of word2vec
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2016-09-13 09:49:44 +04:30 |
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Mahdi Dibaiee
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bcc22465d6
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fix(xor): better learning rate
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2016-09-10 19:21:52 +04:30 |
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Mahdi Dibaiee
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f379f208db
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fix(crossEntropy): implement crossEntropy' to be used in output layer
fix(softmax'): softmax was not correct
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2016-09-10 17:43:45 +04:30 |
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Mahdi Dibaiee
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c23fd14771
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chore: section
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2016-09-10 01:22:09 +04:30 |
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Mahdi Dibaiee
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6cb130b15e
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chore(README): simple neural network
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2016-09-10 01:20:08 +04:30 |
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Mahdi Dibaiee
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58851611dc
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chore(README): better readme, chart
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2016-09-10 01:15:38 +04:30 |
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Mahdi Dibaiee
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b26347e19f
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feat(notmnist): notmnist example using SGD + learning rate decay
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2016-09-10 00:36:15 +04:30 |
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Mahdi Dibaiee
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ace0a18653
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chore(README): explain how the top 10 method increases accuracy and F measure
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2016-08-21 01:21:42 +04:30 |
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Mahdi Dibaiee
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7d0ce29ba8
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chore(README): don't tell them about accuracy, let them try it themselves
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2016-08-21 01:07:01 +04:30 |
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Mahdi Dibaiee
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25e44d3a8c
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chore(data): doc-classifier-data
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2016-08-21 01:02:45 +04:30 |
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Mahdi Dibaiee
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891f48a2d0
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feat(topten): top-ten classification with evenly distrubuted data
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2016-08-21 00:59:42 +04:30 |
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Mahdi Dibaiee
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b2888417bb
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fix(cleanText): remove unnecessary spaces
fix(run): use `1 - prior` for alpha, no need for smoothing
feat(cleanText): turn all text to lowercase
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2016-08-09 16:04:57 +04:30 |
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Mahdi Dibaiee
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eebf5e0222
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feat(verbose): print more information using -v or --verbose flags
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2016-08-08 12:35:26 +04:30 |
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Mahdi Dibaiee
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099c25e166
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feat(stopwords): removeWords and removeStopwords functions as pre-processors
feat(confidence, WIP): calculate confidence of each classification
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2016-08-08 10:02:26 +04:30 |
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Mahdi Dibaiee
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ea1f05f001
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fix(naivebayes): fix the algorithm to make it actually work
feat(cleanDocuments): preprocess documents, use stemming and stopword elimination for better accuracy
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2016-08-05 23:54:36 +04:30 |
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Mahdi Dibaiee
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3cf0625794
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fix(precision): little bug in implementation
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2016-07-30 16:52:34 +04:30 |
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Mahdi Dibaiee
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76e7e7faef
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fix(recall, precision): little bug in calculations
feat(fmeasure): calculate fmeasure using recall and precision
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2016-07-29 22:09:30 +04:30 |
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Mahdi Dibaiee
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812717522e
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refactor(&&&): use &&& instead of the arrow function
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2016-07-29 18:20:35 +04:30 |
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Mahdi Dibaiee
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b5b4629318
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feat(results): accuracy, recall and precision functions used to calculate measures
fix: read data from another repository
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2016-07-29 17:55:59 +04:30 |
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Mahdi Dibaiee
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eeabe4696c
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chore(README): simple initial README
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2016-07-29 16:26:50 +04:30 |
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Mahdi Dibaiee
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26eb4531fa
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feat(naivebayes): implement NaiveBayes algorithm
feat(example): a document classifier using NaiveBayes over reuters data
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2016-07-29 16:16:44 +04:30 |
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Mahdi Dibaiee
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493a20eb0a
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feat(crossEntropy): crossEntropy cost function
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2016-07-24 10:48:04 +04:30 |
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Mahdi Dibaiee
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49606406d1
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fix(run): I had written logistic' wrong, that's what happens when you write code while sleepy
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2016-07-20 12:06:19 +04:30 |
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Mahdi Dibaiee
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b941580273
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chore
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2016-07-20 10:16:13 +04:30 |
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Mahdi Dibaiee
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f5a0c23d99
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feat(randomNetwork): generate random networks with a simple function
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2016-07-18 17:07:12 +04:30 |
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Mahdi Dibaiee
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23851a85f5
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fix(stack): use stack build and exec instead of manual stack ghc
refactor: rename from Lib to Sibe
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2016-07-18 16:33:34 +04:30 |
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Mahdi Dibaiee
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4397f5203a
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fix(train): fix an error in computing layer's error
feat(examples): add an example (xor)
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2016-07-18 00:30:17 +04:30 |
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Mahdi Dibaiee
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763faef434
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fix(session): missing n definition throws error
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2016-07-17 17:14:50 +04:30 |
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Mahdi Dibaiee
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fb01d936c2
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Merge branch 'master' of github.com:mdibaiee/sibe
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2016-07-17 16:54:16 +04:30 |
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Mahdi Dibaiee
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59ab00e9c2
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initial commit, still work in progress
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2016-07-17 16:53:13 +04:30 |
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Mahdi Dibaiee
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ba301efb29
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Initial commit
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2016-07-17 16:52:16 +04:30 |
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