📚 node [[tensor|tensor]]
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⥅ related node [[node_(tensorflow_graph)]]
⥅ related node [[rank_(tensor)]]
⥅ related node [[shape_(tensor)]]
⥅ related node [[tensor flow course master page]]
⥅ related node [[tensor]]
⥅ related node [[tensor_processing_unit_(tpu)]]
⥅ related node [[tensor_rank]]
⥅ related node [[tensor_shape]]
⥅ related node [[tensor_size]]
⥅ related node [[tensorboard]]
⥅ related node [[tensorflow]]
⥅ related node [[tensorflow_playground]]
⥅ related node [[tensorflow_serving]]
⥅ node [[tensor]] pulled by Agora

Tensor

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#TensorFlow

The primary data structure in TensorFlow programs. Tensors are N-dimensional (where N could be very large) data structures, most commonly scalars, vectors, or matrices. The elements of a Tensor can hold integer, floating-point, or string values.

⥅ node [[tensor-flow-course-master-page]] pulled by Agora

Tensor Flow Course Master Page

#TensorFlow

See [[The Golem Project Overview]], the [[Main AI Page]], the [[Python - Main Page]], and the [[Master Contents Page]].

Also see the [[AI Glossary]] for conceptual help.

Tensor Flow 2.0: Deep Learning and Artificial Intelligence

The course material and videos are at Udemy, where the course is hosted.

⥅ node [[tensor_processing_unit_(tpu)]] pulled by Agora

Tensor Processing Unit (TPU)

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#TensorFlow #GoogleCloud

An application-specific integrated circuit (ASIC) that optimizes the performance of machine learning workloads. These ASICs are deployed as multiple TPU chips on a TPU device.

⥅ node [[tensor_rank]] pulled by Agora
⥅ node [[tensor_shape]] pulled by Agora

Tensor shape

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#TensorFlow

The number of elements a Tensor contains in various dimensions. For example, a [5, 10] Tensor has a shape of 5 in one dimension and 10 in another.

⥅ node [[tensor_size]] pulled by Agora

Tensor size

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#TensorFlow

The total number of scalars a Tensor contains. For example, a [5, 10] Tensor has a size of 50.

⥅ node [[tensorboard]] pulled by Agora

TensorBoard

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#TensorFlow

The dashboard that displays the summaries saved during the execution of one or more TensorFlow programs.

⥅ node [[tensorflow]] pulled by Agora

TensorFlow

Go back to the [[AI Glossary]]

#TensorFlow

A large-scale, distributed, machine learning platform. The term also refers to the base API layer in the TensorFlow stack, which supports general computation on dataflow graphs.

Although TensorFlow is primarily used for machine learning, you may also use TensorFlow for non-ML tasks that require numerical computation using dataflow graphs.

See the [[Tensor Flow Course Master Page]]

⥅ node [[tensorflow_playground]] pulled by Agora

TensorFlow Playground

Go back to the [[AI Glossary]]

#TensorFlow

A program that visualizes how different hyperparameters influence model (primarily neural network) training. Go to http://playground.tensorflow.org to experiment with TensorFlow Playground.

⥅ node [[tensorflow_serving]] pulled by Agora
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