[url]http://www.kdnuggets.com/2015/11/google-tensorflow-deep-learning-disappoints.html[/url] said:
Although I was learning how to use TensorFlow, I was finding it difficult to figure out when I would use it. Skimming through the rest of the tutorials, I could see that TensorFlow could be used to implement recurrent neural networks, convolutional neural networks, logistic regression, even Mandelbrot Set generation and visualization (which muddied the picture even further for me, to be honest), but there didn't seem to be any silver bullet (or anything close) as to why I would choose TensorFlow for a given project. I didn't get it. So I dug around further.
Some quick Google-fu and it became evident that I was all alone. There were experts everywhere espousing the benefits of TensorFlow. Well, actually, they were talking about how good it was, but with little more substance than you could find on the TensorFlow website. But at least there were reasons given as to why we should use it... right? Well, actually, not so much. I couldn't find a single use case specifically for TensorFlow anywhere. Most "tech experts" were busy focusing on how TensorFlow would "change everything," and speaking vaguely about how AI and machine learning would now be accessible to anyone who wanted to use it (finally!), and how it can run on a plethora of hardware. Honestly, it seemed like a lot of people were doing their very best to not offend Google, without really understanding what's going on, and perhaps just having heard about deep learning for the first time last week. And no, despite my academic tendencies, I will not be citing anyone here. And I still didn't get it.