TensorFlow

TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks.[4][5]

Quick facts: Developer(s), Initial release, Stable release... ▼

TensorFlow

Developer(s)	Google Brain Team[1]
Initial release	November 9, 2015; 7 years ago (2015-11-09)
Stable release	2.11.0[2]  (18 November 2022; 4 months ago (18 November 2022))
Repository	github.com/tensorflow/tensorflow
Written in	Python, C++, CUDA
Platform	Linux, macOS, Windows, Android, JavaScript[3]
Type	Machine learning library
License	Apache License 2.0
Website	www.tensorflow.org

Part of a series on
Machine learning and data mining
Paradigms Supervised learning Unsupervised learning Online learning Batch learning Meta-learning Semi-supervised learning Self-supervised learning Reinforcement learning Rule-based learning Quantum machine learning
Problems Classification Regression Clustering dimension reduction density estimation Anomaly detection Data Cleaning AutoML Association rules Semantic analysis Structured prediction Feature engineering Feature learning Learning to rank Grammar induction Ontology learning
Supervised learning (classification • regression) Decision trees Ensembles Bagging Boosting Random forest k-NN Linear regression Naive Bayes Artificial neural networks Logistic regression Perceptron Relevance vector machine (RVM) Support vector machine (SVM)
Clustering BIRCH CURE Hierarchical k-means Fuzzy Expectation–maximization (EM) DBSCAN OPTICS Mean shift
Dimensionality reduction Factor analysis CCA ICA LDA NMF PCA PGD t-SNE SDL
Structured prediction Graphical models Bayes net Conditional random field Hidden Markov
Anomaly detection RANSAC k-NN Local outlier factor Isolation forest
Artificial neural network Autoencoder Cognitive computing Deep learning DeepDream Multilayer perceptron RNN LSTM GRU ESN reservoir computing Restricted Boltzmann machine GAN SOM Convolutional neural network U-Net Transformer Vision Spiking neural network Memtransistor Electrochemical RAM (ECRAM)
Reinforcement learning Q-learning SARSA Temporal difference (TD) Multi-agent Self-play
Learning with humans Active learning Crowdsourcing Human-in-the-loop
Model diagnostics Learning curve
Theory Kernel machines Bias–variance tradeoff Computational learning theory Empirical risk minimization Occam learning PAC learning Statistical learning VC theory
Machine-learning venues NeurIPS ICML ICLR ML JMLR
Related articles Glossary of artificial intelligence List of datasets for machine-learning research Outline of machine learning
v t e

TensorFlow was developed by the Google Brain team for internal Google use in research and production.[6][7][8] The initial version was released under the Apache License 2.0 in 2015.[1][9] Google released the updated version of TensorFlow, named TensorFlow 2.0, in September 2019.[10]

TensorFlow can be used in a wide variety of programming languages, including Python, JavaScript, C++, and Java.[11] This flexibility lends itself to a range of applications in many different sectors.