Home » org.tensorflow » tensorflow-lite-gpu » 2.7.0-rc0

TensorFlow Lite » 2.7.0-rc0

A library helps deploy machine learning models on mobile devices

LicenseApache 2.0
Tagsgputensorflowmachine-learning
HomePage https://tensorflow.org/lite/ 🔍 Inspect URL
DateOct 08, 2021
Filespom (1 KB)  aar (4.7 MB)  View All
RepositoriesCentral
Ranking#11444 in MvnRepository (See Top Artifacts)
Used By43 artifacts

Note: There is a new version for this artifact

New Version2.17.0

Scope:
Scope:
Format:
Scope:
Scope:
Scope:
Scope:
Scope:
Scope:

Compile Dependencies (0)

Category/License Group / ArtifactVersionUpdates

Licenses

LicenseURL
The Apache Software License, Version 2.0 http://www.apache.org/licenses/LICENSE-2.0.txt

Developers

NameEmailDev IdRolesOrganization
TensorFlow AuthorsTensorFlow

Related Books

Machine Learning Algorithms in DepthMachine Learning Algorithms in Depth (2025)
by Smolyakov, Vadim
Ultimate Java for Data Analytics and Machine Learning: Unlock Java's Ecosystem for Data Analysis and Machine Learning Using WEKA, JavaML, JFreeChart, and Deeplearning4j (English Edition)Ultimate Java for Data Analytics and Machine Learning: Unlock Java's Ecosystem for Data Analysis and Machine Learning Using WEKA, JavaML, JFreeChart, and Deeplearning4j (English Edition) (2024)
by Kumar, Abhishek
Architecting Data and Machine Learning Platforms: Enable Analytics and AI-Driven Innovation in the CloudArchitecting Data and Machine Learning Platforms: Enable Analytics and AI-Driven Innovation in the Cloud (2023)
by Tranquillin, Marco, Lakshmanan, Valliappa, Tekiner, Firat
Machine Learning System Design InterviewMachine Learning System Design Interview (2023)
by Aminian, Ali, Xu, Alex
Applied Machine Learning and AI for Engineers: Solve Business Problems That Can't Be Solved AlgorithmicallyApplied Machine Learning and AI for Engineers: Solve Business Problems That Can't Be Solved Algorithmically (2022)
by Prosise, Jeff
Deep Learning with TensorFlow and Keras: Build and deploy supervised, unsupervised, deep, and reinforcement learning models, 3rd EditionDeep Learning with TensorFlow and Keras: Build and deploy supervised, unsupervised, deep, and reinforcement learning models, 3rd Edition (2022)
by Kapoor, Amita, Gulli, Antonio, Pal, Sujit, Chollet, Francois
Designing Machine Learning Systems: An Iterative Process for Production-Ready ApplicationsDesigning Machine Learning Systems: An Iterative Process for Production-Ready Applications (2022)
by Huyen, Chip
Machine Learning Engineering in ActionMachine Learning Engineering in Action (2022)
by Wilson, Ben
TensorFlow 2 Pocket Reference: Building and Deploying Machine Learning ModelsTensorFlow 2 Pocket Reference: Building and Deploying Machine Learning Models (2021)
by Tung, KC
Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOpsMachine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps (2020)
by Lakshmanan, Valliappa, Robinson, Sara, Munn, Michael
TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power MicrocontrollersTinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers (2020)
by Warden, Pete, Situnayake, Daniel
Machine Learning in Java: Helpful techniques to design, build, and deploy powerful machine learning applications in Java, 2nd EditionMachine Learning in Java: Helpful techniques to design, build, and deploy powerful machine learning applications in Java, 2nd Edition (2018)
by Bhatia, AshishSingh, Kaluza, Bostjan
Learning TensorFlow: A Guide to Building Deep Learning SystemsLearning TensorFlow: A Guide to Building Deep Learning Systems (2017)
by Hope, Tom, Resheff, Yehezkel S., Lieder, Itay