Search Results for "keras"
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Showing 6 open source projects for "keras"
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Incredable is the first DLT-secured platform that allows you to save time, eliminate errors, and ensure your organization is compliant all in one place.Incredable streamlines and simplifies the complex process of medical credentialing for hospitals and medical facilities, helping you save valuable time, reduce costs, and minimize risks. With Incredable, you can effortlessly manage all your healthcare providers and their credentials within a single, unified platform. Our state-of-the-art technology ensures top-notch data security, giving you peace of mind.
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tvm
Open deep learning compiler stack for cpu, gpu, etc.
...The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. Compilation of deep learning models in Keras, MXNet, PyTorch, Tensorflow, CoreML, DarkNet and more. Start using TVM with Python today, build out production stacks using C++, Rust, or Java the next day. -
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Horovod
Distributed training framework for TensorFlow, Keras, PyTorch, etc.
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data... -
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KotlinDL
High-level Deep Learning Framework written in Kotlin
KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning models in production environments. -
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MMdnn
Tools to help users inter-operate among deep learning frameworks
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks, which means you can train a model with one framework and deploy it with another. ... -
Dun and Bradstreet Risk Analytics - Supplier IntelligenceRisk, procurement, and compliance teams across the globe are under pressure to deal with geopolitical and business risks. Third-party risk exposure is impacted by rapidly scaling complexity in domestic and cross-border businesses, along with complicated and diverse regulations. It is extremely important for companies to proactively manage their third-party relationships. An AI-powered solution to mitigate and monitor counterparty risks on a continuous basis, this cutting-edge platform is powered by D&B’s Data Cloud with 520M+ Global Business Records and 2B+ yearly updates for third-party risk insights. With high-risk procurement alerts and multibillion match points, D&B Risk Analytics leverages best-in-class risk data to help drive informed decisions. Perform quick and comprehensive screening, using intelligent workflows. Receive ongoing alerts of key business indicators and disruptions.
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TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems. Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the theory of transfer learning and show how to apply it in useful projects. ... -
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TenorSpace.js
Neural network 3D visualization framework
TensorSpace is a neural network 3D visualization framework built using TensorFlow.js, Three.js and Tween.js. TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information. After preprocessing the model, TensorSpace supports the visualization of pre-trained models from TensorFlow, Keras and TensorFlow.js. ...
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