Archives for interoperability across frameworks
Modern large-scale automation systems integrate thousands to hundreds of data points. Demands for more flexible reconfiguration of production systems and optimisation across different information models, standards and legacy systems challenge current system interoperability concepts. According to experts, this has become an increasingly important problem that needs to be addressed to fulfil these demands in a…
The post Rethinking The Way We Do Machine Learning: An Engineering Perspective appeared first on Analytics India Magazine.
Modern large-scale automation systems integrate thousands to hundreds of data points. Demands for more flexible reconfiguration of production systems and optimisation across different information models, standards and legacy systems challenge current system interoperability concepts. According to experts, this has become an increasingly important problem that needs to be addressed to fulfil these demands in a…
The post Rethinking The Way We Do Machine Learning: An Engineering Perspective appeared first on Analytics India Magazine.
There’s one aspect that has affected the growth of deep learning research — the proliferation of deep learning frameworks. Popular Deep Learning frameworks such as TensorFlow (Google), PyTorch (one of the newest frameworks that is rapidly gaining popularity), Caffe, MXNet and Keras among others have helped DL researchers achieve human-level efficiencies on tasks such as…
The post Why Tech Giants Are Pinning Their AI Strategy On Deep Learning Frameworks appeared first on Analytics India Magazine.