Alluxio, data orchestration for analytics and machine learning in the cloud
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Updated
Feb 18, 2025 - Java
TensorFlow is an open source library that was created by Google. It is used to design, build, and train deep learning models.
Alluxio, data orchestration for analytics and machine learning in the cloud
AI + Data, online. https://vespa.ai
An Engine-Agnostic Deep Learning Framework in Java
🔥 A library for cropping image in a smart way that can identify the border and correct the cropped image. 智能图片裁剪框架。自动识别边框,手动调节选区,使用透视变换裁剪并矫正选区;适用于身份证,名片,文档等照片的裁剪。
🔥🔥🔥色情图片离线识别,基于TensorFlow实现。识别只需20ms,可断网测试,成功率99%,调用只要一行代码,从雅虎的开源项目open_nsfw移植,该模型文件可用于iOS、java、C++等平台
AI on Hadoop
Machine Learning Platform and Recommendation Engine built on Kubernetes
Android TensorFlow MachineLearning Example (Building TensorFlow for Android)
This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.
Android TensorFlow Lite Machine Learning Example
TensorFlow android demo 车道线 车辆 人脸 动作 骨架 识别 检测 抽烟 打电话 闭眼 睁眼
TonY is a framework to natively run deep learning frameworks on Apache Hadoop.
Deep Learning on Flink aims to integrate Flink and deep learning frameworks (e.g. TensorFlow, PyTorch, etc) to enable distributed deep learning training and inference on a Flink cluster.
Classify camera images locally using TensorFlow models
Android TensorFlow MachineLearning MNIST Example (Building Model with TensorFlow for Android)
通用深度学习推理工具,可在生产环境中快速上线由TensorFlow、PyTorch、Caffe框架训练出的深度学习模型。
DistilBERT / GPT-2 for on-device inference thanks to TensorFlow Lite with Android demo apps
A TensorFlow inference library for react native
Android Chinese TTS Engine Base On Tensorflow TTS , use for TfLite Models Test。安卓离线中文TTS引擎,在TensorflowTTS基础上开发,用于TfLite模型测试。
Handwritten digits classification from MNIST with TensorFlow on Android; Featuring Tutorial!
Created by Google Brain Team
Released November 9, 2015