DeepLearningKit is an Open Source with Apache 2.0 License. It is a Deep Learning Framework for Apple’s iOS, OS X and tvOS that is available at github.com/DeepLearningKit/DeepLearningKit.
Artificial Neural Network Software
For iOS, tvOS, OS X,
Supports (Deep) Convolutional Neural Networks
Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)
DeepLearningKit is an Open Source with Apache 2.0 License. It is a Deep Learning Framework for Apple’s iOS, OS X and tvOS that is available at github.com/DeepLearningKit/DeepLearningKit. The goal is to support using pre-trained Deep Learning models on all Apple’s devices that have GPU(s). It is developed in Swift to easily run on all platforms such as iOS, OS X and tvOS and Metal to efficiently use on-device GPU to ensure low-latency Deep Learning calculations.DeepLearningKit currently supports using (Deep) Convolutional Neural Networks, such as for image recognition, trained with the Caffe Deep Learning Framework but the long term goal is to support using deep learning models trained with the most popular Deep Learning frameworks such as TensorFlow and Torch.The goal of DeepLearningKit is to support using deep learning models trained with popular frameworks such as Caffe, TensorFlow, Torch, Deeplearning4J, Theano, Pylearn and Mocha. Given the massive GPU resources and time required to train Deep Learning models we suggest an App Store like model to distribute and download pre trained and reusable Deep Learning models. Users are welcome to make their contributions and to support DeepLearningKit. There are also video tutorials available in order to use the program on different devices while feedbacks are always welcome.DeepLearningKit
You may also live to read, Predictive Analytics Freeware Software, Top Predictive Analytics proprietary Software, Predictive Analytics Software API, Top Free Data Mining Software, Top Data Mining Software,and Data Ingestion Tools.
More Information on Predictive Analysis Process
For more information of predictive analytics process, please review the overview of each components in the predictive analytics process: data collection (data mining), data analysis, statistical analysis, predictive modeling and predictive model deployment.