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Created with Raphaël 2.2.06Nov51Oct30Apr252414Feb729Oct6Sep23Aug22Jul20Jun614May87614Feb26Sep17Jul611Apr911Feb522Jan21201615Sep543Aug219Jul76512Jun96130May281714Feb111016Jan1411435Dec15Oct5426Sep2315Aug13Jul31May2611Apr54Mar26Feb23Jan22212018Dec161110330Nov261928Aug16Jul151413116Jun22May212018121187624Mar131296543128Feb26241918171110765432131Jan3029282726232219181514131226Dec1511954327Nov21206429Oct2415Sep141242128Aug27222124Jun2327May262322Pickle iVectorMachinePickle GMMStatsPickling KMeansMerge branch 'dask-pipelines' into 'master'Removed Z-T-ZT Normalization from this packageSerialized ISVMachineIncreased latest version to 2.1.7b0 [skip ci]Increased stable version to 2.1.6v2.1.6v2.1.6Updated badges section [ci skip]Updated badges section [ci skip]Removed dependency with bob.pipelinesChanged test functionPickling ISV BaseTemporally add bob.pipelines as dependency [conda]Removed unecessary moduleMaking GMMMachine picklableIncreased latest version to 2.1.6b0 [skip ci]Increased stable version to 2.1.5v2.1.5v2.1.5add debugging messagesbob_em_trainbob_em_trainIncreased latest version to 2.1.5b0 [skip ci]Increased stable version to 2.1.4v2.1.4v2.1.4Merge branch 'issue-31' into 'master'Fixing possible issue with numpy.ndarray.resizeImprovements to the em train scriptFix the import for the moved functionIncreased latest version to 2.1.4b0 [skip ci]Increased stable version to 2.1.3v2.1.3v2.1.3Add a bob em train script which works on SGEMerge branch 'multiprocessing' into 'master'Implemented TV in parallelTurn nitpicky back onbump versionAutomatically create threadpool and allow custom trainersTested kmeans parallelFix error on numpy zero creationFix broken elseMerge branch 'multiprocessing' of gitlab.idiap.ch:bob/bob.learn.em into multiprocessingFixed GIL issueMachines are not thread safe?The data can be GMMStats not just numpy arrays
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