Overview
TensorFlow is an open-source machine-learning platform created by Google’s Brain team. It offers a unified set of tools, libraries and community resources that help researchers and engineers build, train and deploy ML models at scale.
Key Features
- Flexible APIs – High-level Keras interface for fast prototyping and low-level ops for full control.
- Multi-language support – Official bindings for Python, C++, Java, JavaScript and Go, plus community ports for other languages.
- Distributed training – Data-parallel and model-parallel strategies on CPUs, GPUs and TPUs, including parameter-server and Multi-Worker MirroredStrategy support.
- Production deployment – TensorFlow Serving, TensorFlow Lite (mobile / embedded) and TensorFlow.js (browser / Node.js) streamline inference on diverse targets.
- Rich ecosystem – TensorBoard for visualization, TF-Hub for reusable modules, TFX for MLOps pipelines and the Model Garden for reference implementations.
- Active community & governance – Backed by Google, with thousands of open-source contributors and frequent releases.
Typical Use-Cases
Computer vision, NLP, time-series forecasting, reinforcement learning, generative models and research prototypes that need to scale to production.
Licensing
Released under the Apache 2.0 license, TensorFlow can be freely used in commercial and academic projects.
