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Seems like anyone who reads this can try this out. So, through some slightly different set of programs you can even rectify the problem of 'not categorising coloured images' I guess. Isn't it?

Honestly, this is one of your few posts that I gave some attention to read. All other posts are technically too hard to understand man. :)

You can train ANN for any objective. By the way I omitted lot of math. Back propagation is challenging to understand in my opinion. 😃

Pretty cool! I've tried tensorflow few months ago using "TensorFlow for poets", it's an amazing tool for beginners! I trained it with Starwars characters as well as cathedrals to test the limits. A fun thing to do is to test a picture that has nothing to do with the dataset (an apple for example) and see how it reacts.

I look forward to your next article :)

I keep meaning to play with this stuff more. I've done the tensorflow tutorials and need to find a signifiant, but low pressure, project.

There's a lot of great stuff out there that would help me professionally - particularly removal of background noise, feature identification, and segmentation.

I'm also personally curious in text summarization, adversarial networks, and have a special place in my heart for watching videos of reinforcement learning networks figuring out how to play video games.

Cool. I am also interested in neural network powered molecular dynamics which is another area which is getting more attention these days.

I'm also personally curious in text summarization

Will it help you curate steemit better?

I'm just starting to get into molecular dynamics. Well, sorta. I've been following some nice work simulating microbial interactions which uses LAMMPS as a base.

For some reason, text summarization never occurred to me in relation to steemit. But now that I'm thinking about it, document classification could be useful.

That sounds great.

Nice article. FYI, @trufflepig uses a random forest instead of an ANN or some Deep Learning Architecture, less tweaking and no need for heavy lifting CPUs or even GPUs :-D

Oh. Is it? That's cool. So random forest is a computationally inexpensive ML algorithm. I am yet to learn that. Thank you.

By the way, those who want to install these libraries in python I recommend installing Anaconda package. Let me know if any of you have doubts regarding this. These deep learning libraries have capability to run on CPUs and GPUs. I have used CPU version. For larger data sets and deep networks GPUs will accelerate the pace of training.

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