Difference between revisions of "TensorFlow"
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− | [[wikipedia:TensorFlow]] (2015) software library | + | [[wikipedia:TensorFlow]] (2015) software library written in Python, C++, [[CUDA]]. |
+ | |||
+ | [[brew install]] tensorflow | ||
+ | [[pip3 install tensorflow]] | ||
[[import]] * as tf from "@tensorflow/tfjs-node"; | [[import]] * as tf from "@tensorflow/tfjs-node"; | ||
+ | |||
+ | [[import tensorflow as tf]] | ||
== Related terms == | == Related terms == | ||
* [[Artificial neural network]] | * [[Artificial neural network]] | ||
* [[CUDA]] | * [[CUDA]] | ||
+ | * [[Keras]] | ||
+ | * [[numpy]] | ||
+ | * [[Apache MXNet]] | ||
+ | * [[TensorRT]] | ||
== See also == | == See also == | ||
+ | * {{TensorFlow}} | ||
* {{ML}} | * {{ML}} | ||
+ | * {{NN}} | ||
* {{AI}} | * {{AI}} | ||
[[Category:Computing]] | [[Category:Computing]] | ||
+ | [[Category:ML]] | ||
+ | [[Category:TensorFlow]] |
Latest revision as of 16:09, 5 February 2024
wikipedia:TensorFlow (2015) software library written in Python, C++, CUDA.
brew install tensorflow pip3 install tensorflow
import * as tf from "@tensorflow/tfjs-node";
import tensorflow as tf
Related terms[edit]
See also[edit]
- TensorFlow, TPU
- Machine learning, Deep learning, AWS Sagemaker, PyTorch, Kubeflow, TensorFlow, Keras, Torch, Spark ML, Tinygrad, Apple Neural Engine, Scikit-learn, MNIST, MLOps, AutoML, ClearML, PostgresML, AWS Batch, Transformer, Diffusion, Backpropagation, JAX, Vector database, LLM, The Forrester Wave: AI/ML Platforms
- Artificial neural networks, Neuronal network (NN), CNN, Micrograd, NPU, ConvNet, AlexNet, GoogLeNet, Apache MXNet, Neural architecture search, DAG, Feedforward neural network, NeurIPS, Feature Pyramid Network, TPU, NPU, Apple Neural Engine (ANE), LLM, TFLOPS
- AI: Autonomous driving, OpenAI, Google AI,Eliezer Yudkowsky, DeepMind, Computer Vision, Neural network, Vertex AI, Instadeep, Deep learning, Infogrid, Sapling, AssemblyAI, V7, MTIA, Yann LeCun, AI WiW, Salesforce AI, Pika, Amazon Q, LLM, Ollama, Cloud AI Developer Services, Hugging Face, Databricks
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