What is Reddit's opinion of TensorFlow?

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A bunch of modern examples:

http://tensorflow.org/tutorials

And a web-based visualizer:

http://tensorflow.org/how_tos/summaries_and_tensorboard/index.md

Now just show us that Google can continue to maintain an OSS project well over time, and I'll be quite impressed.

This is awesome. Have been doing some of the tutorials and read through part of the how-tos.

Does anyone here know where I can get the Tensor~~Flow~~Board visualization tool? It is mentioned in one of the howtos, but I can't find it anywhere.

EDIT: Never mind, it was included in the default installation but I simply couldn't find the script's location. I had to do > python /usr/local/lib/python2.7/dist-packages/tensorflow/tensorboard/tensorboard.py --logdir=path/to/log-directory

So if I understand that correctly the library isn't really about machine intelligence but for building an infrastructure with multiple computers via network to then build the machine intelligence ...

Edit: They have an interesting tutorial about Convolutional Neural Networks: http://tensorflow.org/tutorials/deep_cnn/index.md

Edit2: bluebaron seems to be correct. Guess they removed the network part before making it open source.

Python seems to be de facto language for different kinds of research. Machine Learning and AI is one where python is huge. The TensorFlow deep learning framework that Google just opensourced has a python api, for example. More info about it here

Your data actually is technically labelled by virtue of being in labelled folders. There's a way using the tf.keras.utils.image_dataset_from_directory to import your images and the folder names as their labels and generate a tf.data.Dataset object. The tensorflow api docs have more info and it's used in a few tutorials across the site (all linked from this page)

Personally, I work on TensorFlow; specifically, on TensorBoard.

I find that most people are already broadly familiar with the idea of AI and Machine Learning (it's in the news a lot :P). So, I tell them that I build tools to make it easier for people who are researching and building AIs to understand what their programs are doing, and how they can improve them. It helps that TensorFlow is public and open source, so I can always show them TensorBoard directly and they can get a feel for it.

This is awesome. Have been doing some of the tutorials and read through part of the how-tos.

Does anyone here know where I can get the Tensor~~Flow~~Board visualization tool? It is mentioned in one of the howtos, but I can't find it anywhere.

EDIT: Never mind, it was included in the default installation but I simply couldn't find the script's location. I had to do > python /usr/local/lib/python2.7/dist-packages/tensorflow/tensorboard/tensorboard.py --logdir=path/to/log-directory

This is the sort of move that has potential to ignite exponential growth in automation capabilities. Millions of smart developers given access an advanced toolkit on which to learn from, extend and take the project in directions Google has yet to. Interesting times ahead I think.

The project site is here <strong>Tensorflow</strong>

I'd start with this tutorial http://tensorflow.org/tutorials/seq2seq/

Replace the 'English text' with your questions, and the 'French text' with your answers.

That should perform reasonably well and will be a good start for tweaking and improvements.

If you've never used tensorflow before, note that Linux is probably the best platform to run on, and that while it will run without a GPU, performance will be terrible.

Oooo, I see. The colors are shifting because it's training that's being visualized. Is that what you're asking? Here's the tutorial I followed for more information:

http://tensorflow.org/tutorials/mnist/beginners/index.html#mnist-for-ml-beginners

This is awesome. Have been doing some of the tutorials and read through part of the how-tos.

Does anyone here know where I can get the Tensor~~Flow~~Board visualization tool? It is mentioned in one of the howtos, but I can't find it anywhere.

EDIT: Never mind, it was included in the default installation but I simply couldn't find the script's location. I had to do > python /usr/local/lib/python2.7/dist-packages/tensorflow/tensorboard/tensorboard.py --logdir=path/to/log-directory

You're trying to build a classification model for images, so it's probably best to use the standard way to do that. For this, I'd recommend the tensorflow-image-classification tutorial.

That said, you might want to look at your implementation first. I would check if your data is correctly labeled (using the correct feature extraction and feature normalization routines) and then do all the steps for text classification. If that's not the case, then you might want to do those steps as well, and then have fun trying the other one. That'll make sure you get it right.

LSTM has a lot of additional optimisations, e.g. LSTM with LSTM and batch normalization can achieve 0.01% speedup. A lot of benchmarks also use LSTM, and some of them are on http://tensorflow.org/performance page.

>if a robot can reprogram himself, then he has free will and isn't following any programming. It's his choice to do an action, because he could always choose to reprogram himself before every action.

Ok... I'm fine with redefining free-will that way if you want. I guess you can say that I've written many programs with free-will then. You should download TensorFlow and try it yourself!

>You have the wrong moral intuition and should reprogram yourself then.

Given what you have told me about your moral intuitions, this is the logical position for you to take. It is logical for me to take the opposite view.

>If you disagree, then you're allowing for everyone to be morally correct and there are no wrong moral intuitions.

I don't know how you're using "correct" here. Do you mean objectively correct?

> Recursion/loops using Enter/Leave/NextIteration control flow constructs. Nice way to do recurrent stuff, I still have to look at the examples to see how it plays out.

I see them in the code, but not in

http://tensorflow.org/api_docs/python/control_flow_ops.md

Am I looking in the wrong place?