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TENSORFLOW

End-to-end open-source machine learning framework

Apache-2.0

ABOUT

Building and deploying machine learning models requires a unified framework for data pipeline construction, model training, distributed computing, and production serving. TensorFlow provides an end-to-end platform with eager execution, automatic differentiation, Keras integration, TFX for production pipelines, TensorFlow Serving for model deployment, and TensorFlow Lite for mobile devices — giving teams a single stack that covers experimentation through deployment.

INSTALL
pip install tensorflow

INTEGRATION GUIDE

1. Train deep neural networks for computer vision, NLP, and generative AI across GPU and TPU clusters 2. Deploy trained models to production using TensorFlow Serving, TF Lite, and TF.js for web 3. Build data preprocessing pipelines using tf.data for efficient input loading at scale 4. Develop and experiment with custom model architectures using eager execution and Keras APIs 5. Run distributed training across multiple GPUs and machines with tf.distribute.Strategy

TAGS

machine-learningdeep-learningpythontensorflowneural-networksgputraininginference