The neural network field enjoys now a resurgence of interest. New training techniques made training deep networks feasible. With deeper networks, more training data and powerful new hardware to make it all work, deep neural networks (or “deep learning” systems) suddenly began making rapid progress in areas such as speech recognition, image classification and language translation. [1]

As result of this there are many posts or websites over the web with the source code and tutorials for neural networks of different types and complexity. Starting from simple feedforward network with just one hidden layer the authors of blog posts or tutorials are helping us to understand how to build neural net (deep or shallow).

To help to find needed python source code for neural network with desired features the website Neural Networks with Python on the Web was created.

Please feel free to add any comments, suggestions or advise the link to neural network web page (python source code) via the comments box on this page.

**References**

1. Why artificial intelligence is enjoying a renaissance

*Related*

Hi, here are a couple of resources that you may wish to add to your list:

http://adventuresinmachinelearning.com/neural-networks-tutorial/ – this one is a really comprehensive introduction to building neural networks in Python.

http://adventuresinmachinelearning.com/python-tensorflow-tutorial/ – this one is a gentle introduction to TensorFlow deep learning in Python also.

Andy – thanks for the links, I will add to database when I will add all other links – sometimes in few weeks.

hi

i saw your pso coding, can u explain how to do it for text data set contains comments about product(sentiment analysis)

Also suggest some books for text mining using matlab.

hi

i saw your pso coding and explaination it is nice, can u explain how to extract best feature for text data set contains comments about product(sentiment analysis)using pso and aco

Also suggest some books for text mining using matlab.

Hi ssmadhu,

To use PSO in text mining you just need define function (fitness function) to optimize. For example in clustering it could be SUM of all distances from each data to its centroid and it should be minimal. After converting text to numerical representation and having function you can apply PSO. I have actually posts (I put below links) that are showing examples how to do clustering with PSO , post 4 is using text data, converting to numerical.

For sentiment analysis you would need probably do classification instead of clustering. Still classification should be similar – define function and apply PSO as usually.

http://intelligentonlinetools.com/blog/2016/07/29/bio-inspired-optimization-for-text-mining-1/

http://intelligentonlinetools.com/blog/2016/08/03/bio-inspired-optimization-for-text-mining-2/

http://intelligentonlinetools.com/blog/2016/08/13/bio-inspired-optimization-for-text-mining-3/

http://intelligentonlinetools.com/blog/2016/08/26/bio-inspired-optimization-for-text-mining-4/

I am not sure about text mining book with MATLAB as I never used MATLAB.

Thanks.