0.7.0 Train deep networks

This is the first release containing passing unit tests that train deep neural networks. The release uses a new implementation of the mini-batch back propagation algorithm originally developed by @davytorres and refactored by @rouson. The new algorithm uses arrays structured differently from previous versions of Inference-Engine. In this release, every procedure has been refactored to eliminate all references to the previous array structures. This refactoring also results in considerable speedup of the test suite.

What's Changed

• Fix terminology by @rouson in #59
• Fix construction from json by @rouson in #60
• Add copyright statements by @rouson in #62
• ci: use newer version of gcc by @everythingfunctional in #64
• Train deep networks by @rouson in #63
• Make trainable_engine_t independent by @rouson in #65
• Refactor tests to use the new data structure by @rouson in #66
• Refactor: remove legacy component arrays in inference_engine_t by @rouson in #67
• Remove inference strategies and integrate netCDF file I/O into library & test suite by @rouson in #68

Full Changelog: 0.6.2...0.7.0