[mlpack] Introduction

[Samrat Patel]

Hello Mlpack Community,
I am Samrat from Delhi Technology University and currently, I am pursuing
my bachelor's in Computer Engineering(CoE). I have 3 years of experience in
C++. I am extremely eager and excited about contributing to various
projects of mlpack. I am willing to participate in GSOC'21 with mlpack.
I would feel indebted if you could guide me in this regard.

Regards
Samrat Patel
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[mlpack] Introduction: Aditya Kandekar, BTech(3rd Year), IIT Guwahati, India

[Aditya Kandekar]

Hi everyone,

I am Aditya Kandekar, prefinal year engineering undergrad at Indian Institute 
of Technology Guwahati. I found "mlpack" in GSoC organisations list and became 
very interested to be the part of the community. I want to contribute to mlpack 
and would like to learn about open sourcing and projects from all of the 
members as I am only a beginner in open-source.  I am familiar with statistics, 
maths and machine learning algorithms. I am also comfortable with C++ and have 
basic knowledge of data structure and algorithms. I hope I'll be a good fit for 
the community here and would like to have some suggestions on how to get 
started.

Thanks!

Aditya Kandekar
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Re: [mlpack] Introduction and Help

[Ryan Curtin]

On Mon, Mar 16, 2020 at 02:25:58PM +0530, ajay wayase wrote:
> I am Ajay Wayase , final year student of Computer Engineering at Pune
> Institute Of Computer Technology and incoming data analyst at Rakuten
> Mobile,Tokyo. I would like to work with mlpack for the GSoc20. Can you
> please provide me some more details about projects and procedures ?

Hi Ajay,

Thanks for getting in touch.  Have you taken a look at the following two
pages?

https://mlpack.org/community.html
https://mlpack.org/gsoc.html

I think you might find those to be helpful resources.

Thanks!

Ryan

-- 
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r...@ratml.org |  - Frank
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[mlpack] Introduction and Help

[ajay wayase]

I am Ajay Wayase , final year student of Computer Engineering at Pune
Institute Of Computer Technology and incoming data analyst at Rakuten
Mobile,Tokyo. I would like to work with mlpack for the GSoc20. Can you
please provide me some more details about projects and procedures ?

Thank you!
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[mlpack] Introduction and a little query

[rupesh mishra]

Greetings,
My name is Rupesh Mishra. I am an undergraduate student from IT branch
currently in my second year. I have been fascinated by the growing field of
machine learning and AI in the past few months.
I just wanted to know that what level of C++ should I have for the
Essential Deep Learning Modules project of MLPACK.
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Re: [mlpack] Introduction

[Adeel Ahmad]

Hi Durgesh,

Welcome to the mlpack community! I would say the first step would be to try and 
build mlpack from source on your machine. This will be required if you want to 
make additions to the library. I found this guide helpful: 
https://github.com/mlpack/mlpack#4-building-mlpack-from-source. Or, if you just 
want to test out some of the tools mlpack offers, you can simply install using 
the package manager. On Ubuntu, this can be achieved with the following command:

$ sudo apt-get install libmlpack-dev


Once you are somewhat familiar with the codebase (going through the tests will 
help you understand the program structure), you can move onto solving a bug 
from the issues list (https://github.com/mlpack/mlpack/issues). It would be 
helpful if you have already decided on a project idea 
(https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas), so you can direct 
your efforts on a particular area. Also, please go through the design 
guidelines (https://github.com/mlpack/mlpack/wiki/DesignGuidelines) before 
submitting your code, this will give you some insight on how to structure your 
contributions.


Let me know if you have any questions.

Thanks,
Adeel




From: mlpack <mlpack-boun...@lists.mlpack.org> on behalf of Durgesha Agrawal 
<dragrawal1...@gmail.com>
Sent: Monday, February 19, 2018 9:57 AM
To: mlpack@lists.mlpack.org
Subject: [mlpack] Introduction

Hello everyone! I am Durgesh Agrawal, first year undergrad from IIT Kanpur. I 
was exposed to machine learning in December and I found it very fascinating and 
interesting. I have completed the Machine learning course by Prof. Andrew Ng 
and I am halfway through the deep learning specialization as well. As of now, I 
am hungry to implement my knowledge to real life problems. I would love to work 
in developing MLPack!
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[mlpack] Introduction to GSOC 2018 : Rohan Rajadhyax

[Rohan Rajadhyax]

My name is Rohan Rajadhyax and I am a fourth year engineering
undergraduate student from Mumbai,India.I am interested in applying for
GSoC and contributing for MLpack library.
I have completed some courses on Python,alogrithms and neutral networks
from MIT ocw,NPTEL and I have a research experience in the field of machine
learning and image processing.I am currently working of analysis of
hyperspectral images using k means clustering.
I'm new to open source field and interested in exploring it.
I'm interested in working on RBFN for GSOC 2018.May I get some leads on
this topic.
After setting up the environment for the required and following the
instructions on the contributing to mlpack page.I started implementing
simple command line executable to understand the process.
Currently I'm reference to the following sites for further information.
Introduction to Radial Basis Function Networks
https://www.cc.gatech.edu›rbf-intro

https://youtu.be/KiVJkqac82Q

I'm interested in working on this idea for GSOC 2018.Kindly consider me for
the project.
Regards,
Rohan Rajadhyax
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Re: [mlpack] Introduction GSoc 2018

[Rahul Barnwal]

Yeah, it finally did. It seemed i didn't add the path variable right.

Thank you for the help.

Regards
Rahul


‌

On Mon, Dec 11, 2017 at 1:29 AM, Evgeny Freyman 
wrote:

> Seems that it still can't find the libmlpack.so. Try calling this before
> building (check that there is a mlpack library at specified path)
>
> export LD_LIBRARY_PATH="/usr/local/lib/:$LD_LIBRARY_PATH"
>
> Another option is to specify location of library thorough -L parameter
> (g++  -L/usr/local/lib/, https://stackoverflow.com/
> questions/6141147/how-do-i-include-a-path-to-libraries-in-g
> 
> )
>
> Could this help?
>
> P.S. It's better to answer all for history and for others to see/comment
>
> Eugene
>
>
> вс, 10 дек. 2017 г. в 20:32, Rahul Barnwal :
>
>> Hi Eugene,
>>
>> Thank you for the help. I am using all the dependencies mentioned to
>> avoid any further unresolved reference problems. But the command
>>
>> g++ -std=c++11 cov.cpp -lmlpack -larmadillo -lboost_serialization
>> -lboost_program_options -lboost_unit_test_framework
>>
>> gives
>>
>> /tmp/cc8qLLm3.o: In function `main':
>> cov.cpp:(.text+0x3aa): undefined reference to `bool
>> mlpack::data::Load(std::__cxx11::basic_string> std::char_traits, std::allocator > const&, arma::Mat&,
>> bool, bool)'
>> collect2: error: ld returned 1 exit status
>>
>> How to remove this unresolved reference problem. Am i missing any other
>> dependencies ?
>> Once again, thank you for the suggestions.
>>
>> Regards
>> Rahul
>>
>>
>>
>>
>>
>>
>> ‌
>>
>> On Sun, Dec 10, 2017 at 9:53 PM, Evgeny Freyman 
>> wrote:
>>
>>> Hi Rahul,
>>>
>>> Just getting started with MLPack myself and had the similar problem. The
>>> solution is:
>>>
>>> 1. As far as I know gcc is for C and g++ is for C++ language, so you
>>> need to use g++
>>> 2. You didn't specify dependencies, thats why you got lots of unresolved
>>> references. The proper way to compile your code is:
>>>
>>> g++ -std=c++11 cov.cpp -lmlpack -larmadillo -lboost_serialization
>>> -lboost_program_options -lboost_unit_test_framework
>>>
>>> granted that you installed MLPack (ran "make install" command from the
>>> instructions). Some of those Boost's dependencies may be redundant here, it
>>> depends on what you use in your code.
>>>
>>> Be careful to specify your source files before list of dependencies.
>>> Thanks *rcurtin *for clarification.
>>>
>>> All the best
>>> Eugene Freyman
>>>
>>>
>>> вс, 10 дек. 2017 г. в 16:46, Rahul Barnwal :
>>>
 Hi,
 I am a fourth year undergraduate student at Indian Institute of
 Technology, Kharagpur, India. I am interested in contributing to mlpack
 library. I am new to open source field and want to explore it in area of
 interest and hence, mlpack.

 Following the instructions given on *contributing to mlpack* page, i
 have compiled it from the source and have also tried some of the simple
 command line executables like mlpack_linear_regression.  But while
 implementing simple mlpack programs, i am stuck.
 i gave this command:
  gcc -std=c++11 cov.cpp
 But got this error instead,  *https://pastebin.com/cb8aKRKf
 *
  Could you please let me know what is wrong here ?


 --
 Regards,
 Rahul Barnwal
 4th year Undergraduate
 Mathematics Department
 IIT KHARAGPUR



 ‌
  Sent with Mailtrack
 
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 mlpack@lists.mlpack.org
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>>>
>>>
>>
>>
>> --
>> Regards,
>> Rahul Barnwal
>> 4th year Undergraduate
>> Mathematics Department
>> IIT KHARAGPUR
>>
>


-- 
Regards,
Rahul Barnwal
4th year Undergraduate
Mathematics Department
IIT KHARAGPUR
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Re: [mlpack] Introduction GSoc 2018

[Evgeny Freyman]

Seems that it still can't find the libmlpack.so. Try calling this before
building (check that there is a mlpack library at specified path)

export LD_LIBRARY_PATH="/usr/local/lib/:$LD_LIBRARY_PATH"

Another option is to specify location of library thorough -L parameter (g++
 -L/usr/local/lib/,
https://stackoverflow.com/questions/6141147/how-do-i-include-a-path-to-libraries-in-g
)

Could this help?

P.S. It's better to answer all for history and for others to see/comment

Eugene


вс, 10 дек. 2017 г. в 20:32, Rahul Barnwal :

> Hi Eugene,
>
> Thank you for the help. I am using all the dependencies mentioned to avoid
> any further unresolved reference problems. But the command
>
> g++ -std=c++11 cov.cpp -lmlpack -larmadillo -lboost_serialization
> -lboost_program_options -lboost_unit_test_framework
>
> gives
>
> /tmp/cc8qLLm3.o: In function `main':
> cov.cpp:(.text+0x3aa): undefined reference to `bool
> mlpack::data::Load(std::__cxx11::basic_string std::char_traits, std::allocator > const&, arma::Mat&,
> bool, bool)'
> collect2: error: ld returned 1 exit status
>
> How to remove this unresolved reference problem. Am i missing any other
> dependencies ?
> Once again, thank you for the suggestions.
>
> Regards
> Rahul
>
>
>
>
>
>
> ‌
>
> On Sun, Dec 10, 2017 at 9:53 PM, Evgeny Freyman 
> wrote:
>
>> Hi Rahul,
>>
>> Just getting started with MLPack myself and had the similar problem. The
>> solution is:
>>
>> 1. As far as I know gcc is for C and g++ is for C++ language, so you need
>> to use g++
>> 2. You didn't specify dependencies, thats why you got lots of unresolved
>> references. The proper way to compile your code is:
>>
>> g++ -std=c++11 cov.cpp -lmlpack -larmadillo -lboost_serialization
>> -lboost_program_options -lboost_unit_test_framework
>>
>> granted that you installed MLPack (ran "make install" command from the
>> instructions). Some of those Boost's dependencies may be redundant here, it
>> depends on what you use in your code.
>>
>> Be careful to specify your source files before list of dependencies.
>> Thanks *rcurtin *for clarification.
>>
>> All the best
>> Eugene Freyman
>>
>>
>> вс, 10 дек. 2017 г. в 16:46, Rahul Barnwal :
>>
>>> Hi,
>>> I am a fourth year undergraduate student at Indian Institute of
>>> Technology, Kharagpur, India. I am interested in contributing to mlpack
>>> library. I am new to open source field and want to explore it in area of
>>> interest and hence, mlpack.
>>>
>>> Following the instructions given on *contributing to mlpack* page, i
>>> have compiled it from the source and have also tried some of the simple
>>> command line executables like mlpack_linear_regression.  But while
>>> implementing simple mlpack programs, i am stuck.
>>> i gave this command:
>>>  gcc -std=c++11 cov.cpp
>>> But got this error instead,  *https://pastebin.com/cb8aKRKf
>>> *
>>>  Could you please let me know what is wrong here ?
>>>
>>>
>>> --
>>> Regards,
>>> Rahul Barnwal
>>> 4th year Undergraduate
>>> Mathematics Department
>>> IIT KHARAGPUR
>>>
>>>
>>>
>>> ‌
>>>  Sent with Mailtrack
>>> 
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>>> 
>>
>>
>
>
> --
> Regards,
> Rahul Barnwal
> 4th year Undergraduate
> Mathematics Department
> IIT KHARAGPUR
>
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Re: [mlpack] Introduction GSoc 2018

[Evgeny Freyman]

Hi Rahul,

Just getting started with MLPack myself and had the similar problem. The
solution is:

1. As far as I know gcc is for C and g++ is for C++ language, so you need
to use g++
2. You didn't specify dependencies, thats why you got lots of unresolved
references. The proper way to compile your code is:

g++ -std=c++11 cov.cpp -lmlpack -larmadillo -lboost_serialization
-lboost_program_options -lboost_unit_test_framework

granted that you installed MLPack (ran "make install" command from the
instructions). Some of those Boost's dependencies may be redundant here, it
depends on what you use in your code.

Be careful to specify your source files before list of dependencies.
Thanks *rcurtin
*for clarification.

All the best
Eugene Freyman


вс, 10 дек. 2017 г. в 16:46, Rahul Barnwal :

> Hi,
> I am a fourth year undergraduate student at Indian Institute of
> Technology, Kharagpur, India. I am interested in contributing to mlpack
> library. I am new to open source field and want to explore it in area of
> interest and hence, mlpack.
>
> Following the instructions given on *contributing to mlpack* page, i have
> compiled it from the source and have also tried some of the simple command
> line executables like mlpack_linear_regression.  But while implementing
> simple mlpack programs, i am stuck.
> i gave this command:
>  gcc -std=c++11 cov.cpp
> But got this error instead,  *https://pastebin.com/cb8aKRKf
> *
>  Could you please let me know what is wrong here ?
>
>
> --
> Regards,
> Rahul Barnwal
> 4th year Undergraduate
> Mathematics Department
> IIT KHARAGPUR
>
>
>
> ‌
>  Sent with Mailtrack
> 
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[mlpack] Introduction GSoc 2018

[Rahul Barnwal]

Hi,
I am a fourth year undergraduate student at Indian Institute of Technology,
Kharagpur, India. I am interested in contributing to mlpack library. I am
new to open source field and want to explore it in area of interest and
hence, mlpack.

Following the instructions given on *contributing to mlpack* page, i have
compiled it from the source and have also tried some of the simple command
line executables like mlpack_linear_regression.  But while implementing
simple mlpack programs, i am stuck.
i gave this command:
 gcc -std=c++11 cov.cpp
But got this error instead,  *https://pastebin.com/cb8aKRKf
*
 Could you please let me know what is wrong here ?


-- 
Regards,
Rahul Barnwal
4th year Undergraduate
Mathematics Department
IIT KHARAGPUR



‌
 Sent with Mailtrack

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[mlpack] Introduction

[KUSHAL BORKAR]

Greetings All,
   My name is Kushal Borkar. I'm from India and currently
I'm pursuing Bachelor's Degree in Electronics and Communication. I have
basic knowledge of c++ and python. I would love to contribute and learn
from 'ml pack' as this will be my first time working with an organization.
Can someone please guide me how to contribute and where to contribute as
I'm new to Git hub and I'm also looking for GSoC 2018.

Thanking All,

Kushal Borkar
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[mlpack] Introduction and request for guidance

[vamsi b]

Hey,
I am Vamsi an undergrad student from India studying in Indian Institute of
Technology Indore. I am new to mlpack and machine learning as a whole but
am very excited to learn and contribute to mlpack. I would also like to
take contribute to mlpack as part of GSOC 2018. Any person in this list
familiar with the repository (not necessarily related to GSOC) and willing
to help me out, kindly reply back to me. Any small help is appreciated.
Thanks,
Vamsi Bulusu (vamsib...@gmail.com)
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Re: [mlpack] Introduction of ExecutionPolicy

[Ryan Curtin]

On Tue, May 16, 2017 at 09:30:52PM +0530, Ankit Aggarwal wrote:
> Hi Shikhar
> 
> Just a tip
> 
> Please avoid using *"auto t0 = std::chrono::high_resolution_clock::now();*"
> and rather use* gettimeofday* for any kind of benchmarking as if you
> measure the performance of these two function you will find out that
> high_resolution_clock to be atleast 2-3x slower than gettimeofday.I know
> you are taking the difference but it will help if you require some kind of
> book-keeping of time events to avoid latency.

There's also Timer::Start() and Timer::Stop() which might be a little
more convenient, if you want to drag the rest of mlpack in too. :)
Personally I like to use those when I am benchmarking for simplicity.

It seems to me like the idea of the policy is to determine how many
cores to use, but I think maybe OpenMP already has some support for
this.  For instance, if I write an OpenMP-ized program called 'program',
I can specify the number of cores it should use as an environment
variable:

$ OMP_NUM_THREADS=2 ./program

By default the number of threads used will be the maximum on the
machine, but this environment variable gives the user some nice
standardized control over the way the programs are executed.  I think
most users who see software that's parallelized with OpenMP interpret
this as the standard way to control its behavior.

You can also use omp_set_num_threads(...):

// The number of cores we want to use.
#define N 4

int main()
{
  omp_set_num_threads(N);

  // the rest of the program
  // ...
}

So I think maybe some of the support you need is already there.  Let me
know what you think.

Thanks,

Ryan

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Re: [mlpack] Introduction of ExecutionPolicy

[Ankit Aggarwal]

Hi Shikhar

Just a tip

Please avoid using *"auto t0 = std::chrono::high_resolution_clock::now();*"
and rather use* gettimeofday* for any kind of benchmarking as if you
measure the performance of these two function you will find out that
high_resolution_clock to be atleast 2-3x slower than gettimeofday.I know
you are taking the difference but it will help if you require some kind of
book-keeping of time events to avoid latency.

Ankit Aggarwal

On Tue, May 16, 2017 at 8:52 PM, Shikhar Bhardwaj <
shikharbhardwa...@gmail.com> wrote:

> Hello everyone,
>
> Yannis and I were discussing about the introduction of an ExecutionPolicy 
> policy parameter in algorithms implemented by mlpack to provide parallel 
> overloads of the algorithms as template specializations.
>
> This approach is a bit similar to C++'s planned support for "Extensions of 
> Parallelism" , 
> describing 3 types of execution policies and overloads of various std 
> algorithms with these execution policies.
>
> In addition to describing the type of execution(parallel/sequential etc), 
> this parameter can also be used to describe other characteristics of the 
> execution, the number of threads used during the execution being an example.
>
> A rough demo of how the interface would look from the user's perspective is 
> here. 
> 
>
> We wanted to have further discussion about this design. A few existing issues 
> include the current interface, which is quite crude. For example, we need to 
> hardcode the value of the number of threads in the parallel execution policy, 
> instead of taking it directly from somewhere like 
> std::thread::hardware_concurrency.
>
> Would this design be a good one?
>
> Any thoughts?
>
> Thanks
>
> --
> Shikhar Bhardwaj
>
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[mlpack] Introduction

[Krishnakanth Singh]

Hi,
Firstly I want to thank the full community especially Marcus and Ryan for
their support and help
with proposal and getting comfortable with the mlpack code base. I am glad
that i have been given this  amazing opportunity to work on Deep Learning
Modules under Mikhail Lozhnikov.

I am looking forward to a great summer ahead with mlpack. My exams will be
over this week and all my projects work will be over by this weekend. So I
will available from Tuesday to contact with the mentors and discuss about
the project and proposal with them.

Thanks again for the great opportunity.


Thanks
KrishnaKant Singh
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[mlpack] Introduction

[Samikshya Chand]

Hi everyone !
I am Samikshya Chand (github name *sam0410*), undergraduate sophomore at
Indian Institute of Technology, Varanasi (IIT BHU) of the Electronics
branch.
I have been involved with mlpack over the last 2 months and I have been
contributing since the last month.
I am interested in contributing to mlpack in GSOC 2017 in the project
"Better Benchmarking".
I have shared my proposal at GsoC website. I request the mentors for giving
their feedback, if there is time.

Regards,
Samikshya.

-- 
Samikshya Chand
B.Tech. Part-II
Electronics Engineering
IIT-BHU (Varanasi)
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Re: [mlpack] Introduction for GSoC 2017

[Ryan Curtin]

On Tue, Mar 14, 2017 at 11:09:42PM +0530, Saumya Sachdev wrote:
> Hello to everyone at mlpack!
> 
> My name is Saumya Sachdev and I am a Computer Science Engineering student
> at PES Institute of Technology, Bangalore, India. I am currently in my
> second year of the degree course. I want to participate in Google Summer of
> Code 2017 with mlpack. I went through the list of projects and I would like
> to work on one of the following:
> 
> 1. Essential Deep Learning Modules
> 2. Reinforcement Learning
> 
> I am currently undertaking the Machine Learning course by Andrew Ng on
> Coursera. I am also working on a project which is about Network Text
> Analysis of Online Conversations for Marketing Intelligence which uses
> clustering algorithms to summarize text.
> 
> To prepare for this project I am planning to do the Deep Learning course on
> Udacity. I have also installed mlpack on my system and would like to start
> contributing to it.
> 
> Please help me understand the library better and guide me to what I need to
> do in order to prepare for the project.

Hi Saumya,

The deep learning modules and reinforcement learning projects have
gotten a lot of attention this year.  If you are looking to submit an
application for either of these, I would suggest you start by looking at
these two pages:

http://www.mlpack.org/gsoc.html
http://www.mlpack.org/involved.html

and then for specific information on the two projects you mentioned
interest in, you might consider searching the mailing list archives:

http://knife.lugatgt.org/pipermail/mlpack/

Here is a post I found with links to many other posts:

http://knife.lugatgt.org/pipermail/mlpack/2017-March/003120.html

I hope this is helpful; let me know if I can clarify anything.

Thanks,

Ryan

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[mlpack] Introduction for GSoC 2017

[Saumya Sachdev]

Hello to everyone at mlpack!

My name is Saumya Sachdev and I am a Computer Science Engineering student
at PES Institute of Technology, Bangalore, India. I am currently in my
second year of the degree course. I want to participate in Google Summer of
Code 2017 with mlpack. I went through the list of projects and I would like
to work on one of the following:

1. Essential Deep Learning Modules
2. Reinforcement Learning

I am currently undertaking the Machine Learning course by Andrew Ng on
Coursera. I am also working on a project which is about Network Text
Analysis of Online Conversations for Marketing Intelligence which uses
clustering algorithms to summarize text.

To prepare for this project I am planning to do the Deep Learning course on
Udacity. I have also installed mlpack on my system and would like to start
contributing to it.

Please help me understand the library better and guide me to what I need to
do in order to prepare for the project.

Thanking you,
Saumya Sachev
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