I spent a good amount of time looking for an ML library written in Go, with a usable API and with active maintenance and the only framework out there is https://github.com/gorgonia/gorgonia which seems tailored to academics need. I wanted a library to embed I could use in a stealth startup I am working on and frankly nothing came close to the quality I was looking for. In particular I wanted something with: 1. Ability to plug in different activation functions. 2. Takes advantage of Goroutines 3. Ability to import weights from other frameworks(TBD in Therfoo) 4. A high level API like Keras 5. A testable architecture Have you used any of the libraries you sent? I would like to hear your experience working with any of them. Perhaps I missed something... I am dog fooding Therfoo in a personal production product at the moment and love the ability of including ML capabilities with under 20 lines of code. Thanks for your feedback. On Tue, Feb 19, 2019 at 22:16 Martin Akolo Chiteri via skunkworks < skunkworks@lists.my.co.ke> wrote:

Hi David,

Any specific reason you are implementing the Deep Learning module from Scratch? There are a couple in existence already, probably well executed and tested. Perhaps you could join those projects and work on bug fixes and enhancements instead ....

https://github.com/josephmisiti/awesome-machine-learning#go http://gopherdata.io/post/deeplearning_in_go_part_1/ https://medium.com/sourcedtech/machine-learning-on-go-code-829e85e2d2c6

Good luck in any case.

Martin.

On Mon, Feb 18, 2019 at 12:40 PM David Njuguna via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

I am currently writing a deep learning Golang module/library - https://github.com/therfoo/therfoo and wondering if anyone here would be open to collaborating on the same?

Kind regards, David Ndungu

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Martin, I did spend months working with Keras + Tensorflow and there was a myriad of issues making that work with my Go software that requires extremely low latency and online training. Let's talk after you have a few years of hands-on experience production building ML solutions and know the difference between academic and production quality software. Thanks. Kind regards, David Ndungu On Wed, Feb 20, 2019 at 2:36 PM Martin Akolo Chiteri via skunkworks < skunkworks@lists.my.co.ke> wrote:

Hi David,

On Wed, Feb 20, 2019 at 11:24 AM David Njuguna via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

I spent a good amount of time looking for an ML library written in Go, with a usable API and with active maintenance and the only framework out there is https://github.com/gorgonia/gorgonia which seems tailored to academics need.

ML is by and for academics and Statisticians [0] in particular. It is only starting to get used outside universities now because of the improvements of performance in Computing hardware [1] experienced in the recent past in my opinion. The statistical learning theory methods have been in existence since 1800s [2] though computing power had always been a physical limit to their success.

I wanted a library to embed I could use in a stealth startup I am working

...

on and frankly nothing came close to the quality I was looking for. In particular I wanted something with:

1. Ability to plug in different activation functions.

Scikit learn's (Python) module for Multi-layer perceptron's algorithms supports nearly all possible activation functions [3] available to nodes in an artificial neural network.

2. Takes advantage of Goroutines

...

3. Ability to import weights from other frameworks(TBD in Therfoo) 4. A high level API like Keras 5. A testable architecture

Have you used any of the libraries you sent?

No, I have not.

I would like to hear your experience working with any of them.

...

I have instead used Python ML libraries (Scikit-Learn) for building different models to predict residual values (market prices) of heavy construction equipment using historical data from equipment auctions and resales. All that was part of my research for my M.Sc thesis [4]

Perhaps I missed something...

...

If you cannot find an adequate ML library in Go, I would encourage you to go with those available in Python (Theano and / or Scikit-Learn) for your project if that is a feasible option. Perhaps you can deal with performance bottlenecks in future as the application scales up. Or maybe find out how to speed the app using different Python libraries to support multi-threading [5]. Another possibility might be to escape into C-mode in Python for the parts of your program that require high performance. Those are my opinions.

...

I am dog fooding Therfoo in a personal production product at the moment and love the ability of including ML capabilities with under 20 lines of code.

Thanks for your feedback.

You are welcome David

[0]: R for Statistical computing https://www.r-project.org/ [1]: Yoshua Bengio https://youtu.be/uawLjkSI7Mo [2]: Least Squares Method of regression analysis https://en.wikipedia.org/wiki/Regression_analysis#History [3]: Python's Sci-kit learn regression using neural networks https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLP... [4]: https://era.library.ualberta.ca/items/71ce7a37-fad3-4e67-97af-912e82bad726/v... [5]: Green threads in Python https://greenlet.readthedocs.io/

Hope that helps.

Martin.

...

On Tue, Feb 19, 2019 at 22:16 Martin Akolo Chiteri via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

Hi David,

Any specific reason you are implementing the Deep Learning module from Scratch? There are a couple in existence already, probably well executed and tested. Perhaps you could join those projects and work on bug fixes and enhancements instead ....

https://github.com/josephmisiti/awesome-machine-learning#go http://gopherdata.io/post/deeplearning_in_go_part_1/ https://medium.com/sourcedtech/machine-learning-on-go-code-829e85e2d2c6

Good luck in any case.

Martin.

On Mon, Feb 18, 2019 at 12:40 PM David Njuguna via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

I am currently writing a deep learning Golang module/library - https://github.com/therfoo/therfoo and wondering if anyone here would be open to collaborating on the same?

Kind regards, David Ndungu

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Hi David, On Wed, Feb 20, 2019 at 4:32 PM David Njuguna via skunkworks < skunkworks@lists.my.co.ke> wrote:

Martin,

BTW, have you heard of Keras Tensorflow or PyTorch?

I have used TensorFlow (TF) a briefly since my projects required other models to be built besides those generated by neural network algorithms. Had no need to use PyTorch though a classmate utilized it for his research. Ran models on a GPU using CUDA https://era.library.ualberta.ca/items/259b6334-68ae-44a7-8e2e-8d69a5d895e4/v...

Kind regards,

David Ndungu

On Wed, Feb 20, 2019 at 3:19 PM David Njuguna <dnjuguna@gmail.com> wrote:

...

Martin,

I did spend months working with Keras + Tensorflow and there was a myriad of issues making that work with my Go software that requires extremely low latency and online training.

Let's talk after you have a few years of hands-on experience production building ML solutions and know the difference between academic and production quality software.

David, I am a professional software developer with about 10 years of experience (8 years in the energy sector + humanitarian work and 2.5 years in academia). Hands-on experience in building production quality ML solutions *is not* *Rocket Science*. Surprisingly, your effort (80 - 90%) will be mostly spent in preparing and cleaning up data before fitting your data to different models using your ML algorithm of choice ...

Go ahead and implement a multi-layer perceptron algorithm from scratch. My opinion is that more people can benefit more from your work if you can improve an existing library for building artificial neural network models. My feedback was given in an effort to be helpful Good luck. Martin.

Thanks.

...

Kind regards, David Ndungu

On Wed, Feb 20, 2019 at 2:36 PM Martin Akolo Chiteri via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

Hi David,

On Wed, Feb 20, 2019 at 11:24 AM David Njuguna via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

I spent a good amount of time looking for an ML library written in Go, with a usable API and with active maintenance and the only framework out there is https://github.com/gorgonia/gorgonia which seems tailored to academics need.

ML is by and for academics and Statisticians [0] in particular. It is only starting to get used outside universities now because of the improvements of performance in Computing hardware [1] experienced in the recent past in my opinion. The statistical learning theory methods have been in existence since 1800s [2] though computing power had always been a physical limit to their success.

I wanted a library to embed I could use in a stealth startup I am

...

working on and frankly nothing came close to the quality I was looking for. In particular I wanted something with:

1. Ability to plug in different activation functions.

Scikit learn's (Python) module for Multi-layer perceptron's algorithms supports nearly all possible activation functions [3] available to nodes in an artificial neural network.

2. Takes advantage of Goroutines

...

3. Ability to import weights from other frameworks(TBD in Therfoo) 4. A high level API like Keras 5. A testable architecture

Have you used any of the libraries you sent?

No, I have not.

I would like to hear your experience working with any of them.

...

I have instead used Python ML libraries (Scikit-Learn) for building different models to predict residual values (market prices) of heavy construction equipment using historical data from equipment auctions and resales. All that was part of my research for my M.Sc thesis [4]

Perhaps I missed something...

...

If you cannot find an adequate ML library in Go, I would encourage you to go with those available in Python (Theano and / or Scikit-Learn) for your project if that is a feasible option. Perhaps you can deal with performance bottlenecks in future as the application scales up. Or maybe find out how to speed the app using different Python libraries to support multi-threading [5]. Another possibility might be to escape into C-mode in Python for the parts of your program that require high performance. Those are my opinions.

...

I am dog fooding Therfoo in a personal production product at the moment and love the ability of including ML capabilities with under 20 lines of code.

Thanks for your feedback.

You are welcome David

[0]: R for Statistical computing https://www.r-project.org/ [1]: Yoshua Bengio https://youtu.be/uawLjkSI7Mo [2]: Least Squares Method of regression analysis https://en.wikipedia.org/wiki/Regression_analysis#History [3]: Python's Sci-kit learn regression using neural networks https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLP... [4]: https://era.library.ualberta.ca/items/71ce7a37-fad3-4e67-97af-912e82bad726/v... [5]: Green threads in Python https://greenlet.readthedocs.io/

Hope that helps.

Martin.

...

On Tue, Feb 19, 2019 at 22:16 Martin Akolo Chiteri via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

Hi David,

Any specific reason you are implementing the Deep Learning module from Scratch? There are a couple in existence already, probably well executed and tested. Perhaps you could join those projects and work on bug fixes and enhancements instead ....

https://github.com/josephmisiti/awesome-machine-learning#go http://gopherdata.io/post/deeplearning_in_go_part_1/ https://medium.com/sourcedtech/machine-learning-on-go-code-829e85e2d2c6

Good luck in any case.

Martin.

On Mon, Feb 18, 2019 at 12:40 PM David Njuguna via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

I am currently writing a deep learning Golang module/library - https://github.com/therfoo/therfoo and wondering if anyone here would be open to collaborating on the same?

Kind regards, David Ndungu

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_______________________________________________

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David, As I stated earlier, my intention was to offer any sort of help to your situation with ML libraries (lack of) appropriate for training neural network models in Go. I honestly did not know that I was dealing with an ML expert, apologies for that. Yes, I abandoned this repo, https://github.com/chiteri/neural_networks_and_deep_learning. It really does not bother me, why should it disturb you in the least bit of ways? Was simply trying to wrap my head around the material presented in the first chapter of this book http://neuralnetworksanddeeplearning.com/ which I did and moved on with the project that I had at hand. My intention is not to be in any committee of any form, at least not for writing programs. Maybe my message did not reach out with enough clarity but what I said is that I have more familiarity with Python modules that achieve a number of what you need. On top of that if you can recall, I passed a link with several Go libraries that might have been adequate for your purposes in my first response to you. Your inquiry appeared quite straight-forward. I do possess an intuitive understanding of most of the methods I utilize to train machine learning models with. I get results that are adequate for my purposes from them and interpret them accordingly. Am not sure what else needs to be done besides that David? Martin. On Wed, Feb 20, 2019 at 6:25 PM David Njuguna via skunkworks < skunkworks@lists.my.co.ke> wrote:

Martin,

Let me make this clear.

*My Goals:* 1. To benefit those of us who already chose Go and would like to embed ML into their software and would like module with a *high-level* API akin to Keras. There is a reason why Google adopted Keras to the official high-level API for Tensorflow.

*My Non-Goals*: 1. To convince anyone to start using Go in production. 2. To form a *committee* to decide on whether the world needs a new ML library. 3. To find out if I should continue working on Therfoo, that ship has sailed, I am already using it. 4. To debate whether I should port my software from Go to Python or to C

Any specific reason you are implementing *(correction, have implemented...)* the Deep Learning module from Scratch? *admittedly I started writing this to develop my intuition as I studied ML and deep learning. I would presume it the same reason you started (and abandoned...?) https://github.com/chiteri/neural_networks_and_deep_learning <https://github.com/chiteri/neural_networks_and_deep_learning> ?* There are a couple in existence already *(no there are not any production-grade deep learning libraries in Golang**)*, probably well executed and tested. Perhaps you could join those projects and work on bug fixes and enhancements instead ....

https://github.com/josephmisiti/awesome-machine-learning#go *8/12 of the general purpose Go projects on this list are deprecated as for the remaining 4 projects* 1. https://goreportcard.com/report/github.com/znly/go-ml-transpiler* - a D report is not how we do things where I come from* 2. https://goreportcard.com/report/github.com/goml/gobrain - *a C report is not how we do things where I come from* 3. https://github.com/MaxHalford/eaopt *- would be interesting if I was interested in an evolutionary optimization library.*

http://gopherdata.io/post/deeplearning_in_go_part_1/ <- *this is about Gorgonia. The API is too low level for my liking. The project scope much larger than I need.* https://medium.com/sourcedtech/machine-learning-on-go-code-829e85e2d2c6 *<- this is not an ML library. It is an article about a talk at Gophercon 2019, I was there.*

Good luck in any case. *thanks!*

Kind regards, David Ndungu

On Tue, Feb 19, 2019 at 10:16 PM Martin Akolo Chiteri via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

Hi David,

Any specific reason you are implementing the Deep Learning module from Scratch? There are a couple in existence already, probably well executed and tested. Perhaps you could join those projects and work on bug fixes and enhancements instead ....

https://github.com/josephmisiti/awesome-machine-learning#go http://gopherdata.io/post/deeplearning_in_go_part_1/ https://medium.com/sourcedtech/machine-learning-on-go-code-829e85e2d2c6

Good luck in any case.

Martin.

On Mon, Feb 18, 2019 at 12:40 PM David Njuguna via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

I am currently writing a deep learning Golang module/library - https://github.com/therfoo/therfoo and wondering if anyone here would be open to collaborating on the same?

Kind regards, David Ndungu

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BTW, this is besides the point. Most of ML talent is actually being poached from academia all over the world where cutting-edge research is going on on different techniques. 1) Deep Mind in Edmonton, CA: https://deepmind.com/blog/deepmind-office-canada-edmonton/ 2) Facebook AL lab in Montreal, CA: https://www.mcgill.ca/newsroom/channels/news/mcgill-researcher-head-facebook... 3) Richard Sutton U of A, CA: https://www.ualberta.ca/newtrail/featurestories/2018/may/unexpected-insights... 4) David Silver, RL YouTube videos: https://youtu.be/2pWv7GOvuf0 5) Richard Sutton, RL intro: http://incompleteideas.net/book/bookdraft2017nov5.pdf Good day. Martin. On Thu, Feb 21, 2019 at 4:09 AM Solomon Kariri <solomonkariri@gmail.com> wrote:

David,

*Go* ahead and do what you feel you want or might be beneficial to you or someone else (maybe even me in future). If we all worked on fixing/improving what exists, we would still be improving assembly language.

Solomon Kariri,

Software Engineer

On Thu, Feb 21, 2019 at 9:51 AM Martin Akolo Chiteri via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

David,

As I stated earlier, my intention was to offer any sort of help to your situation with ML libraries (lack of) appropriate for training neural network models in Go. I honestly did not know that I was dealing with an ML expert, apologies for that.

Yes, I abandoned this repo, https://github.com/chiteri/neural_networks_and_deep_learning. It really does not bother me, why should it disturb you in the least bit of ways? Was simply trying to wrap my head around the material presented in the first chapter of this book http://neuralnetworksanddeeplearning.com/ which I did and moved on with the project that I had at hand.

My intention is not to be in any committee of any form, at least not for writing programs. Maybe my message did not reach out with enough clarity but what I said is that I have more familiarity with Python modules that achieve a number of what you need. On top of that if you can recall, I passed a link with several Go libraries that might have been adequate for your purposes in my first response to you. Your inquiry appeared quite straight-forward.

I do possess an intuitive understanding of most of the methods I utilize to train machine learning models with. I get results that are adequate for my purposes from them and interpret them accordingly. Am not sure what else needs to be done besides that David?

Martin.

On Wed, Feb 20, 2019 at 6:25 PM David Njuguna via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

Martin,

Let me make this clear.

*My Goals:* 1. To benefit those of us who already chose Go and would like to embed ML into their software and would like module with a *high-level* API akin to Keras. There is a reason why Google adopted Keras to the official high-level API for Tensorflow.

*My Non-Goals*: 1. To convince anyone to start using Go in production. 2. To form a *committee* to decide on whether the world needs a new ML library. 3. To find out if I should continue working on Therfoo, that ship has sailed, I am already using it. 4. To debate whether I should port my software from Go to Python or to C

Any specific reason you are implementing *(correction, have implemented...)* the Deep Learning module from Scratch? *admittedly I started writing this to develop my intuition as I studied ML and deep learning. I would presume it the same reason you started (and abandoned...?) https://github.com/chiteri/neural_networks_and_deep_learning <https://github.com/chiteri/neural_networks_and_deep_learning> ?* There are a couple in existence already *(no there are not any production-grade deep learning libraries in Golang**)*, probably well executed and tested. Perhaps you could join those projects and work on bug fixes and enhancements instead ....

https://github.com/josephmisiti/awesome-machine-learning#go *8/12 of the general purpose Go projects on this list are deprecated as for the remaining 4 projects* 1. https://goreportcard.com/report/github.com/znly/go-ml-transpiler* - a D report is not how we do things where I come from* 2. https://goreportcard.com/report/github.com/goml/gobrain - *a C report is not how we do things where I come from* 3. https://github.com/MaxHalford/eaopt *- would be interesting if I was interested in an evolutionary optimization library.*

http://gopherdata.io/post/deeplearning_in_go_part_1/ <- *this is about Gorgonia. The API is too low level for my liking. The project scope much larger than I need.* https://medium.com/sourcedtech/machine-learning-on-go-code-829e85e2d2c6 *<- this is not an ML library. It is an article about a talk at Gophercon 2019, I was there.*

Good luck in any case. *thanks!*

Kind regards, David Ndungu

On Tue, Feb 19, 2019 at 10:16 PM Martin Akolo Chiteri via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

Hi David,

Any specific reason you are implementing the Deep Learning module from Scratch? There are a couple in existence already, probably well executed and tested. Perhaps you could join those projects and work on bug fixes and enhancements instead ....

https://github.com/josephmisiti/awesome-machine-learning#go http://gopherdata.io/post/deeplearning_in_go_part_1/ https://medium.com/sourcedtech/machine-learning-on-go-code-829e85e2d2c6

Good luck in any case.

Martin.

On Mon, Feb 18, 2019 at 12:40 PM David Njuguna via skunkworks < skunkworks@lists.my.co.ke> wrote:

...

I am currently writing a deep learning Golang module/library - https://github.com/therfoo/therfoo and wondering if anyone here would be open to collaborating on the same?

Kind regards, David Ndungu

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