Explore tweets tagged as #computationgraph
"new projects dispense with #computationgraph-s entirely, to bring #differentiableprogramming to the mainstream". "#Julia is unusually well-suited for expressing #machinelearning algorithm". "#SPMD programming".#automaticDifferentiation.#automaticBatching.#CompilerDesign #ML #DSL
A follow up from the "On Machine Learning and Programming Languages" blog from last year. We have made a bunch of progress and summarize it in a new post "Building a language and compiler for machine learning".
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#LI RT machine_ml RT dataHacker_rs: Secrets About COMPUTATION GRAPH - Example . #deeplearning #dnn #neuralnetwork #logisticregression #computationgraph #machinelearning #ml #rvp #7GTech #ArtificialIntel….
RT @dataHacker_rs: Secrets About COMPUTATION GRAPH - Example . #deeplearning #dnn #neuralnetwork #logisticregression #computationgraph #machinelearning #ml
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MultiLayerNetwork ComputationGraph tutorial with Deeplearning4j. #Java #MachineLearning . Java.
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RT @dataHacker_rs: Secrets About COMPUTATION GRAPH - Example . #deeplearning #dnn #neuralnetwork #logisticregression #computationgraph #machinelearning #ml
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RT @tier1app: RT @java: MultiLayerNetwork ComputationGraph tutorial with Deeplearning4j. #Java #MachineLearning .
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#BigData #ProgrammingModel #DSL #Scala.#ComputationGraph #LinearAlgebra.#DL4J #TensorFlow #ScalaLMS .#CompilerDesign
Staged meta-programming, new LMS frontend and computation graphs
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After all, everything should sum up like this: .def execute_computation_graph(graph: ComputationGraph, data_inputs: List[np.ndarray]) -> np.ndarray:. """. Executes the given computation graph on the decentralized network with provided inputs. """.Democracy of code.
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@deeplearning4j @jasonbaldridge @omidbbb @dlwh @msurd @spacy_io Awesome: Computation Graph API as well! #dlearn.
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Every program that works with #Tensorflow consists #computationgraph .#run #computationgraph . #ML #MachineLearning.
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#Pytorch is a #dynamic #NeuralNetwork kit. In a #StaticToolkit, you define a #ComputationGraph once, compile it, and then stream instances to it. In a #DynamicToolkit, you define a computation graph for each instance. It is never compiled and is executed on-the-fly.
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@ElectMemo NaNになる直前のモデルが欲しいならtrainを書き換えて数epochごとにモデルを書き出す.あとfitの実装見てるんですがどこでNaNが入ってくるのか全然分からんですね。.NaNが出た時点でstack traceとか出てデバッグコードを流し込めるといいんが無理らし.
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We show how penalized estimation and optimization of different fit functions can be easily implemented with this approach, and how our #rstats package #tensorsem, based on #TensorFlow, can estimate these: 3/4.
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some update by Gil and @vikgl about the #computationgraph development happening currently in our library #ngraph #JIT
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