Gradient Descent vs Adagrad vs Momentum in TensorFlow
Question: I'm studyng _TensorFlow_ and how to use it, even if I'm not an expert of
neural network and deep learnig (just the bases).

Following tutorials I don't understand the real and practice difference
between the three optimizers for a loss.

Now I need an advice.

I look at the API
<https://www.tensorflow.org/versions/r0.7/api_docs/python/train.html#optimizers>
and I understand the principles, but my questions are:

**1\. When is preferable use one instead the others ?**

**2\. There are important differences to know ?**


Answer: [Here's a nice explanation](http://sebastianruder.com/optimizing-gradient-
descent/) and comparison of different optimizers (not mine)

