Should I use TensorFlow
Google's Machine Learning framework TensorFlow was open-sourced in November 2015 [1] and has since built a growing community around it. TensorFlow is supposed to be flexible for research purposes while also allowing its models to be deployed productively. This work is aimed towards people with experience in Machine Learning considering whether they should use TensorFlow in their environment. Several aspects of the framework important for such a decision are examined, such as the heterogenity, extensibility and its computation graph. A pure Python implementation of linear classification is compared with an implementation utilizing TensorFlow. I also contrast TensorFlow to other popular frameworks with respect to modeling capability, deployment and performance and give a brief description of the current adaption of the framework.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningGeneral ClassificationSimilar Papers 제목 키워드 기반
CondConv: Conditionally Parameterized Convolutions for Efficient Inference
Convolutional layers are one of the basic building blocks of modern deep neural networks. One fundamental assumption is that convolutional kernels should be shared for all examples in a dataset. We propose conditionally …
General ClassificationImage ClassificationObject DetectionTensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning
TensorFlow Eager is a multi-stage, Python-embedded domain-specific language for hardware-accelerated machine learning, suitable for both interactive research and production. TensorFlow, which TensorFlow Eager extends, re…
BIG-bench Machine LearningDevice Placement Optimization with Reinforcement Learning
The past few years have witnessed a growth in size and computational requirements for training and inference with neural networks. Currently, a common approach to address these requirements is to use a heterogeneous dist…
Language ModelingLanguage ModellingMachine Translationreinforcement-learning+3TensorFlow.js: Machine Learning for the Web and Beyond
TensorFlow.js is a library for building and executing machine learning algorithms in JavaScript. TensorFlow.js models run in a web browser and in the Node.js environment. The library is part of the TensorFlow ecosystem, …
BIG-bench Machine LearningTensorFlow: A system for large-scale machine learning
TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. I…
BIG-bench Machine LearningManagement