## TensorFlow and Deep Learning without a PhD, Part 2 (Google Cloud Next ’17)

1. #### Q World

Thanks a ton, very informative session!

2. #### Eric Graf

Here is the Link to his github code https://github.com/martin-gorner/tensorflow-mnist-tutorial

3. #### Hans Baier

Excellent tutorial. Thanks for sharing!

4. #### Rowan Gontier

Wonderful stuff.

5. #### 大老表

I feel too small, too much things to learn……

6. #### August Karlstedt

Too bad; still getting a PhD 😂

7. #### Ivan Cavattoni

Why CELLSIZE is 512? Is there some reason you choose 512?

8. #### kunwar singh

good work Martin

9. #### Gaurav Singh

After going through so many YouTube videos on Tensorflow, I stumble upon this amazing multi part video series and wow… each concept is explained so clearly in such a precise manner… Thanks a lot Martin!!
Really looking forward to more such Amazing videos from you

10. #### Darkarix

What is the advantage of having a 3 layer network? if the minibatch sequencer has to follow the sentence it practically treats one layer at a time I don't understand how it is improving the training to have them connected, is it just to save computation power or there's more to it??

11. #### Mona Chu

If High School math, a simple linear equation can do such magic in TensorFlow, just think what would the mathematical knowledge of a Mathematician, Physicist, or an engineer would do for AI.

Knowing Quantum computer is now in used, I am so excited and scared, just as scientists first heard an atomic bomb had been detonated.

12. #### Ayman Shams

Is there a lab available for RNN?

14. #### Andrew

Cool scarf bro

15. #### Рудольф Зайдель

Where is part 3? Or where I can find next? Tnx

16. #### Wang Zhe

refer to 3:24, isn't it suppose to be softmax, but the computed probabilities doesn't sum up to 1 in your slide.

17. #### Siddharth Kotwal

Great tutorial, love the first principles thinking. I think this is the first time I've understood how the TF developers were thinking while writing these abstractions for RNNs.

18. #### Martin Görner

The code for all the "Tensorflow without a PhD" sessions is now in a single place on GitHub: https://github.com/GoogleCloudPlatform/tensorflow-without-a-phd
The series now has 6 sessions. You will find the videos and slide decks at the URL above as well.