Conclusion

This report attempted to introduce deep learning and frame core questions around its use and the use of TensorFlow for the enterprise. We first looked at the case for deep learning, especially when compared to more traditional machine learning techniques, and examined some of the state-of-the-art applications for which deep learning technologies have been used. If your organization is interested in using audio, video, image, or free-text data, deep learning is worth exploring. Next, we examined various frameworks for deep learning, with particular attention paid to libraries focused on the enterprise, including Microsoft’s Cognitive Toolkit, MXNet, and Deeplearning4J. Finally, we surveyed the TensorFlow library and the existing ecosystem to understand how various components complement the core capabilities of the library and assist with both network training and inference. We hope that this overview helps decision makers and technology leaders within the enterprise navigate the growing world of deep learning.