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Jelajahi alat untuk mendukung dan mempercepat alur kerja TensorFlow.
Kolaborasi Colaboratory adalah lingkungan notebook Jupyter gratis yang tidak memerlukan penyiapan dan berjalan sepenuhnya di cloud, sehingga Anda dapat mengeksekusi kode TensorFlow di browser dengan satu klik.
Blok Visual Kerangka kerja web pengkodean visual untuk membuat prototipe alur kerja ML menggunakan perangkat I/O, model, augmentasi data, dan bahkan kode Colab sebagai elemen penyusun yang dapat digunakan kembali.
Papan Tensor Serangkaian alat visualisasi untuk memahami, men-debug, dan mengoptimalkan program TensorFlow.
Alat Bagaimana-Jika Alat untuk menyelidiki model pembelajaran mesin tanpa kode, berguna untuk pemahaman model, proses debug, dan keadilan. Tersedia di TensorBoard dan notebook jupyter atau colab.
Kinerja ML Rangkaian tolok ukur ML yang luas untuk mengukur kinerja kerangka perangkat lunak ML, akselerator perangkat keras ML, dan platform cloud ML.
XLA XLA (Accelerated Linear Algebra) adalah compiler khusus domain untuk aljabar linier yang mengoptimalkan komputasi TensorFlow. Hasilnya adalah peningkatan kecepatan, penggunaan memori, dan portabilitas pada server dan platform seluler.
Taman Bermain TensorFlow Bermain-main dengan jaringan saraf di browser Anda. Jangan khawatir, Anda tidak bisa merusaknya.
Awan Penelitian TPU Program TPU Research Cloud (TRC) memungkinkan para peneliti untuk mengajukan permohonan akses ke lebih dari 1.000 Cloud TPU tanpa biaya untuk membantu mereka mempercepat gelombang terobosan penelitian berikutnya.
MLIR Representasi perantara dan kerangka kompiler baru.
[null,null,[],[],[],null,["# Tools\n=====\n\nExplore tools to support and accelerate TensorFlow workflows. \n[Colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb) \nColaboratory is a free Jupyter notebook environment that requires no setup and runs entirely in the cloud, allowing you to execute TensorFlow code in your browser with a single click. \n[Learn more](https://colab.sandbox.google.com/notebooks/welcome.ipynb) \n[Visual Blocks](https://visualblocks.withgoogle.com/) \nA visual coding web framework to prototype ML workflows using I/O devices, models, data augmentation, and even Colab code as reusable building blocks. \n[Learn more](https://visualblocks.withgoogle.com/) \n[TensorBoard](/tensorboard) \nA suite of visualization tools to understand, debug, and optimize TensorFlow programs. \n[Learn more](/tensorboard) [View code](https://github.com/tensorflow/tensorboard) \n[What-If Tool](https://pair-code.github.io/what-if-tool/) \nA tool for code-free probing of machine learning models, useful for model understanding, debugging, and fairness. Available in TensorBoard and jupyter or colab notebooks. \n[Learn more](https://pair-code.github.io/what-if-tool/) [Get started](https://colab.research.google.com/github/PAIR-code/what-if-tool/blob/master/What_If_Tool_Notebook_Usage.ipynb) \n[ML Perf](https://mlperf.org/) \nA broad ML benchmark suite for measuring performance of ML software frameworks, ML hardware accelerators, and ML cloud platforms. \n[Learn more](https://mlperf.org/) \n[XLA](/xla) \nXLA (Accelerated Linear Algebra) is a domain-specific compiler for linear algebra that optimizes TensorFlow computations. The results are improvements in speed, memory usage, and portability on server and mobile platforms. \n[Learn more](/xla) \n[TensorFlow Playground](https://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle®Dataset=reg-plane&learningRate=0.03®ularizationRate=0&noise=0&networkShape=4,2&seed=0.04620&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false) \nTinker with a neural network in your browser. Don't worry, you can't break it. \n[Learn more](https://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle®Dataset=reg-plane&learningRate=0.03®ularizationRate=0&noise=0&networkShape=4,2&seed=0.04620&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false) \n[TPU Research Cloud](https://sites.research.google/trc/) \nThe TPU Research Cloud (TRC) program enables researchers to apply for access to a cluster of more than 1,000 Cloud TPUs at no charge to help them accelerate the next wave of research breakthroughs. \n[Learn more](https://sites.research.google/trc/) \n[MLIR](/mlir) \nA new intermediate representation and compiler framework. \n[Learn more](/mlir) \n\nExplore libraries that build advanced models, methods, and extensions using TensorFlow\n--------------------------------------------------------------------------------------\n\n[See libraries](/resources/libraries-extensions)"]]
