Re: Book for Machine Learning (MLIB and other libraries on Spark)

2016-06-12 Thread Chris Fregly 
two of my faves:

https://www.amazon.com/Advanced-Analytics-Spark-Patterns-Learning/dp/1491912766/
(Cloudera authors)

https://www.amazon.com/Machine-Learning-Spark-Powerful-Algorithms/dp/1783288515/
(IBM author)

(most) authors are Spark Committers.

while not totally up to date w/ ML pipelines and such, these 2 books give
you relevant use cases and make you think about ML in terms of distributed
systems.

classics.

On Sun, Jun 12, 2016 at 7:57 AM, Deepak Goel  wrote:

> Thank You...Please see inline..
>
>
> On Sun, Jun 12, 2016 at 3:39 PM,  wrote:
>
>> Machine learning - I would suggest that you pick up a fine book that
>> explains machine learning. That's the way I went about - pick up each type
>> of machine learning concept - say Linear regression then understand the
>> why/when/how etc and infer results etc.
>>
>> Then apply the learning to a small data set using python or R or scala
>> without Spark. This is to familiarize the learning.
>>
>>
> Then run the same with MLlib and see it with a big data set on Spark. I
>> would call this consolidation.
>>
> *Deepak
>
> Sorry for the confusion in my question. However, I was more interested in
> getting hold of a book which explains how I can use MLlib and Spark for
> machine learning problems.
>
> *Deepak
>
>>
>> Few things to remember - all Machine learning algorithms are not
>> available On spark. There is a list of machine learning supported in spark.
>> Kindly look at that. Also look at how to integrate mahout / h20 with spark
>> and see how you can run the machine learning stuff supported by mahout with
>> spark.
>>
>> And then your journey begins :-).
>>
>> Regards,
>> Harmeet
>>
>>
>>
>>
>> On Jun 12, 2016, at 0:31, Mich Talebzadeh 
>> wrote:
>>
>> yes absolutely Ted.
>>
>> Thanks for highlighting it
>>
>>
>>
>> Dr Mich Talebzadeh
>>
>>
>>
>> LinkedIn * 
>> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
>> *
>>
>>
>>
>> http://talebzadehmich.wordpress.com
>>
>>
>>
>> On 11 June 2016 at 19:00, Ted Yu  wrote:
>>
>>> Another source is the presentation on various ocnferences.
>>> e.g.
>>>
>>> http://www.slideshare.net/databricks/apache-spark-mllib-20-preview-data-science-and-production
>>>
>>> FYI
>>>
>>> On Sat, Jun 11, 2016 at 8:47 AM, Mich Talebzadeh <
>>> mich.talebza...@gmail.com> wrote:
>>>
 Interesting.

 The pace of development in this field is such that practically every
 single book in Big Data landscape gets out of data before the ink dries on
 it  :)

 I concur that they serve as good reference for starters but in my
 opinion the best way to learn is to start from on-line docs (and these are
 pretty respectful when it comes to Spark) and progress from there.

 If you have a certain problem then put to this group and I am sure
 someone somewhere in this forum has come across it. Also most of these
 books' authors actively contribute to this mailing list.


 HTH


 Dr Mich Talebzadeh



 LinkedIn * 
 https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
 *



 http://talebzadehmich.wordpress.com



 On 11 June 2016 at 16:10, Ted Yu  wrote:

>
> https://www.amazon.com/Machine-Learning-Spark-Powerful-Algorithms/dp/1783288515/ref=sr_1_1?ie=UTF8=1465657706=8-1=spark+mllib
>
>
> https://www.amazon.com/Spark-Practical-Machine-Learning-Chinese/dp/7302420424/ref=sr_1_3?ie=UTF8=1465657706=8-3=spark+mllib
>
>
> https://www.amazon.com/Advanced-Analytics-Spark-Patterns-Learning/dp/1491912766/ref=sr_1_2?ie=UTF8=1465657706=8-2=spark+mllib
>
>
> On Sat, Jun 11, 2016 at 8:04 AM, Deepak Goel 
> wrote:
>
>>
>> Hey
>>
>> Namaskara~Nalama~Guten Tag~Bonjour
>>
>> I am a newbie to Machine Learning (MLIB and other libraries on Spark)
>>
>> Which would be the best book to learn up?
>>
>> Thanks
>> Deepak
>>--
>> Keigu
>>
>> Deepak
>> 73500 12833
>> www.simtree.net, dee...@simtree.net
>> deic...@gmail.com
>>
>> LinkedIn: www.linkedin.com/in/deicool
>> Skype: thumsupdeicool
>> Google talk: deicool
>> Blog: http://loveandfearless.wordpress.com
>> Facebook: http://www.facebook.com/deicool
>>
>> "Contribute to the world, environment and more :
>> http://www.gridrepublic.org
>> "
>>
>
>

>>>
>>
>


-- 
*Chris Fregly*
Research Scientist @ PipelineIO
San Francisco, CA
http://pipeline.io

Re: Book for Machine Learning (MLIB and other libraries on Spark)

2016-06-12 Thread Deepak Goel 
Thank You...Please see inline..


On Sun, Jun 12, 2016 at 3:39 PM,  wrote:

> Machine learning - I would suggest that you pick up a fine book that
> explains machine learning. That's the way I went about - pick up each type
> of machine learning concept - say Linear regression then understand the
> why/when/how etc and infer results etc.
>
> Then apply the learning to a small data set using python or R or scala
> without Spark. This is to familiarize the learning.
>
>
Then run the same with MLlib and see it with a big data set on Spark. I
> would call this consolidation.
>
*Deepak

Sorry for the confusion in my question. However, I was more interested in
getting hold of a book which explains how I can use MLlib and Spark for
machine learning problems.

*Deepak

>
> Few things to remember - all Machine learning algorithms are not available
> On spark. There is a list of machine learning supported in spark. Kindly
> look at that. Also look at how to integrate mahout / h20 with spark and see
> how you can run the machine learning stuff supported by mahout with spark.
>
> And then your journey begins :-).
>
> Regards,
> Harmeet
>
>
>
>
> On Jun 12, 2016, at 0:31, Mich Talebzadeh 
> wrote:
>
> yes absolutely Ted.
>
> Thanks for highlighting it
>
>
>
> Dr Mich Talebzadeh
>
>
>
> LinkedIn * 
> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> *
>
>
>
> http://talebzadehmich.wordpress.com
>
>
>
> On 11 June 2016 at 19:00, Ted Yu  wrote:
>
>> Another source is the presentation on various ocnferences.
>> e.g.
>>
>> http://www.slideshare.net/databricks/apache-spark-mllib-20-preview-data-science-and-production
>>
>> FYI
>>
>> On Sat, Jun 11, 2016 at 8:47 AM, Mich Talebzadeh <
>> mich.talebza...@gmail.com> wrote:
>>
>>> Interesting.
>>>
>>> The pace of development in this field is such that practically every
>>> single book in Big Data landscape gets out of data before the ink dries on
>>> it  :)
>>>
>>> I concur that they serve as good reference for starters but in my
>>> opinion the best way to learn is to start from on-line docs (and these are
>>> pretty respectful when it comes to Spark) and progress from there.
>>>
>>> If you have a certain problem then put to this group and I am sure
>>> someone somewhere in this forum has come across it. Also most of these
>>> books' authors actively contribute to this mailing list.
>>>
>>>
>>> HTH
>>>
>>>
>>> Dr Mich Talebzadeh
>>>
>>>
>>>
>>> LinkedIn * 
>>> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
>>> *
>>>
>>>
>>>
>>> http://talebzadehmich.wordpress.com
>>>
>>>
>>>
>>> On 11 June 2016 at 16:10, Ted Yu  wrote:
>>>

 https://www.amazon.com/Machine-Learning-Spark-Powerful-Algorithms/dp/1783288515/ref=sr_1_1?ie=UTF8=1465657706=8-1=spark+mllib


 https://www.amazon.com/Spark-Practical-Machine-Learning-Chinese/dp/7302420424/ref=sr_1_3?ie=UTF8=1465657706=8-3=spark+mllib


 https://www.amazon.com/Advanced-Analytics-Spark-Patterns-Learning/dp/1491912766/ref=sr_1_2?ie=UTF8=1465657706=8-2=spark+mllib


 On Sat, Jun 11, 2016 at 8:04 AM, Deepak Goel  wrote:

>
> Hey
>
> Namaskara~Nalama~Guten Tag~Bonjour
>
> I am a newbie to Machine Learning (MLIB and other libraries on Spark)
>
> Which would be the best book to learn up?
>
> Thanks
> Deepak
>--
> Keigu
>
> Deepak
> 73500 12833
> www.simtree.net, dee...@simtree.net
> deic...@gmail.com
>
> LinkedIn: www.linkedin.com/in/deicool
> Skype: thumsupdeicool
> Google talk: deicool
> Blog: http://loveandfearless.wordpress.com
> Facebook: http://www.facebook.com/deicool
>
> "Contribute to the world, environment and more :
> http://www.gridrepublic.org
> "
>


>>>
>>
>

Re: Book for Machine Learning (MLIB and other libraries on Spark)

2016-06-12 Thread mylisttech 
Machine learning - I would suggest that you pick up a fine book that explains 
machine learning. That's the way I went about - pick up each type of machine 
learning concept - say Linear regression then understand the why/when/how etc 
and infer results etc. 

Then apply the learning to a small data set using python or R or scala without 
Spark. This is to familiarize the learning.

Then run the same with MLlib and see it with a big data set on Spark. I would 
call this consolidation. 

Few things to remember - all Machine learning algorithms are not available On 
spark. There is a list of machine learning supported in spark. Kindly look at 
that. Also look at how to integrate mahout / h20 with spark and see how you can 
run the machine learning stuff supported by mahout with spark.

And then your journey begins :-).

Regards,
Harmeet




On Jun 12, 2016, at 0:31, Mich Talebzadeh  wrote:

> yes absolutely Ted.
> 
> Thanks for highlighting it
> 
> 
> 
> Dr Mich Talebzadeh
>  
> LinkedIn  
> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
>  
> http://talebzadehmich.wordpress.com
>  
> 
> On 11 June 2016 at 19:00, Ted Yu  wrote:
> Another source is the presentation on various ocnferences.
> e.g.
> http://www.slideshare.net/databricks/apache-spark-mllib-20-preview-data-science-and-production
> 
> FYI
> 
> On Sat, Jun 11, 2016 at 8:47 AM, Mich Talebzadeh  
> wrote:
> Interesting.
> 
> The pace of development in this field is such that practically every single 
> book in Big Data landscape gets out of data before the ink dries on it  :)
> 
> I concur that they serve as good reference for starters but in my opinion the 
> best way to learn is to start from on-line docs (and these are pretty 
> respectful when it comes to Spark) and progress from there.
> 
> If you have a certain problem then put to this group and I am sure someone 
> somewhere in this forum has come across it. Also most of these books' authors 
> actively contribute to this mailing list.
> 
> 
> HTH
> 
> 
> Dr Mich Talebzadeh
>  
> LinkedIn  
> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
>  
> http://talebzadehmich.wordpress.com
>  
> 
> On 11 June 2016 at 16:10, Ted Yu  wrote:
> https://www.amazon.com/Machine-Learning-Spark-Powerful-Algorithms/dp/1783288515/ref=sr_1_1?ie=UTF8=1465657706=8-1=spark+mllib
> 
> https://www.amazon.com/Spark-Practical-Machine-Learning-Chinese/dp/7302420424/ref=sr_1_3?ie=UTF8=1465657706=8-3=spark+mllib
> 
> https://www.amazon.com/Advanced-Analytics-Spark-Patterns-Learning/dp/1491912766/ref=sr_1_2?ie=UTF8=1465657706=8-2=spark+mllib
> 
> 
> On Sat, Jun 11, 2016 at 8:04 AM, Deepak Goel  wrote:
> 
> Hey
> 
> Namaskara~Nalama~Guten Tag~Bonjour
> 
> I am a newbie to Machine Learning (MLIB and other libraries on Spark)
> 
> Which would be the best book to learn up?
> 
> Thanks
> Deepak
>-- 
> Keigu
> 
> Deepak
> 73500 12833
> www.simtree.net, dee...@simtree.net
> deic...@gmail.com
> 
> LinkedIn: www.linkedin.com/in/deicool
> Skype: thumsupdeicool
> Google talk: deicool
> Blog: http://loveandfearless.wordpress.com
> Facebook: http://www.facebook.com/deicool
> 
> "Contribute to the world, environment and more : http://www.gridrepublic.org
> "
> 
> 
> 
>

Re: Book for Machine Learning (MLIB and other libraries on Spark)

2016-06-11 Thread Mich Talebzadeh 
yes absolutely Ted.

Thanks for highlighting it



Dr Mich Talebzadeh



LinkedIn * 
https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
*



http://talebzadehmich.wordpress.com



On 11 June 2016 at 19:00, Ted Yu  wrote:

> Another source is the presentation on various ocnferences.
> e.g.
>
> http://www.slideshare.net/databricks/apache-spark-mllib-20-preview-data-science-and-production
>
> FYI
>
> On Sat, Jun 11, 2016 at 8:47 AM, Mich Talebzadeh <
> mich.talebza...@gmail.com> wrote:
>
>> Interesting.
>>
>> The pace of development in this field is such that practically every
>> single book in Big Data landscape gets out of data before the ink dries on
>> it  :)
>>
>> I concur that they serve as good reference for starters but in my opinion
>> the best way to learn is to start from on-line docs (and these are pretty
>> respectful when it comes to Spark) and progress from there.
>>
>> If you have a certain problem then put to this group and I am sure
>> someone somewhere in this forum has come across it. Also most of these
>> books' authors actively contribute to this mailing list.
>>
>>
>> HTH
>>
>>
>> Dr Mich Talebzadeh
>>
>>
>>
>> LinkedIn * 
>> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
>> *
>>
>>
>>
>> http://talebzadehmich.wordpress.com
>>
>>
>>
>> On 11 June 2016 at 16:10, Ted Yu  wrote:
>>
>>>
>>> https://www.amazon.com/Machine-Learning-Spark-Powerful-Algorithms/dp/1783288515/ref=sr_1_1?ie=UTF8=1465657706=8-1=spark+mllib
>>>
>>>
>>> https://www.amazon.com/Spark-Practical-Machine-Learning-Chinese/dp/7302420424/ref=sr_1_3?ie=UTF8=1465657706=8-3=spark+mllib
>>>
>>>
>>> https://www.amazon.com/Advanced-Analytics-Spark-Patterns-Learning/dp/1491912766/ref=sr_1_2?ie=UTF8=1465657706=8-2=spark+mllib
>>>
>>>
>>> On Sat, Jun 11, 2016 at 8:04 AM, Deepak Goel  wrote:
>>>

 Hey

 Namaskara~Nalama~Guten Tag~Bonjour

 I am a newbie to Machine Learning (MLIB and other libraries on Spark)

 Which would be the best book to learn up?

 Thanks
 Deepak
--
 Keigu

 Deepak
 73500 12833
 www.simtree.net, dee...@simtree.net
 deic...@gmail.com

 LinkedIn: www.linkedin.com/in/deicool
 Skype: thumsupdeicool
 Google talk: deicool
 Blog: http://loveandfearless.wordpress.com
 Facebook: http://www.facebook.com/deicool

 "Contribute to the world, environment and more :
 http://www.gridrepublic.org
 "

>>>
>>>
>>
>

Re: Book for Machine Learning (MLIB and other libraries on Spark)

2016-06-11 Thread Ted Yu 
Another source is the presentation on various ocnferences.
e.g.
http://www.slideshare.net/databricks/apache-spark-mllib-20-preview-data-science-and-production

FYI

On Sat, Jun 11, 2016 at 8:47 AM, Mich Talebzadeh 
wrote:

> Interesting.
>
> The pace of development in this field is such that practically every
> single book in Big Data landscape gets out of data before the ink dries on
> it  :)
>
> I concur that they serve as good reference for starters but in my opinion
> the best way to learn is to start from on-line docs (and these are pretty
> respectful when it comes to Spark) and progress from there.
>
> If you have a certain problem then put to this group and I am sure someone
> somewhere in this forum has come across it. Also most of these books'
> authors actively contribute to this mailing list.
>
>
> HTH
>
>
> Dr Mich Talebzadeh
>
>
>
> LinkedIn * 
> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> *
>
>
>
> http://talebzadehmich.wordpress.com
>
>
>
> On 11 June 2016 at 16:10, Ted Yu  wrote:
>
>>
>> https://www.amazon.com/Machine-Learning-Spark-Powerful-Algorithms/dp/1783288515/ref=sr_1_1?ie=UTF8=1465657706=8-1=spark+mllib
>>
>>
>> https://www.amazon.com/Spark-Practical-Machine-Learning-Chinese/dp/7302420424/ref=sr_1_3?ie=UTF8=1465657706=8-3=spark+mllib
>>
>>
>> https://www.amazon.com/Advanced-Analytics-Spark-Patterns-Learning/dp/1491912766/ref=sr_1_2?ie=UTF8=1465657706=8-2=spark+mllib
>>
>>
>> On Sat, Jun 11, 2016 at 8:04 AM, Deepak Goel  wrote:
>>
>>>
>>> Hey
>>>
>>> Namaskara~Nalama~Guten Tag~Bonjour
>>>
>>> I am a newbie to Machine Learning (MLIB and other libraries on Spark)
>>>
>>> Which would be the best book to learn up?
>>>
>>> Thanks
>>> Deepak
>>>--
>>> Keigu
>>>
>>> Deepak
>>> 73500 12833
>>> www.simtree.net, dee...@simtree.net
>>> deic...@gmail.com
>>>
>>> LinkedIn: www.linkedin.com/in/deicool
>>> Skype: thumsupdeicool
>>> Google talk: deicool
>>> Blog: http://loveandfearless.wordpress.com
>>> Facebook: http://www.facebook.com/deicool
>>>
>>> "Contribute to the world, environment and more :
>>> http://www.gridrepublic.org
>>> "
>>>
>>
>>
>

Re: Book for Machine Learning (MLIB and other libraries on Spark)

2016-06-11 Thread Mich Talebzadeh 
Interesting.

The pace of development in this field is such that practically every single
book in Big Data landscape gets out of data before the ink dries on it  :)

I concur that they serve as good reference for starters but in my opinion
the best way to learn is to start from on-line docs (and these are pretty
respectful when it comes to Spark) and progress from there.

If you have a certain problem then put to this group and I am sure someone
somewhere in this forum has come across it. Also most of these books'
authors actively contribute to this mailing list.


HTH


Dr Mich Talebzadeh



LinkedIn * 
https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
*



http://talebzadehmich.wordpress.com



On 11 June 2016 at 16:10, Ted Yu  wrote:

>
> https://www.amazon.com/Machine-Learning-Spark-Powerful-Algorithms/dp/1783288515/ref=sr_1_1?ie=UTF8=1465657706=8-1=spark+mllib
>
>
> https://www.amazon.com/Spark-Practical-Machine-Learning-Chinese/dp/7302420424/ref=sr_1_3?ie=UTF8=1465657706=8-3=spark+mllib
>
>
> https://www.amazon.com/Advanced-Analytics-Spark-Patterns-Learning/dp/1491912766/ref=sr_1_2?ie=UTF8=1465657706=8-2=spark+mllib
>
>
> On Sat, Jun 11, 2016 at 8:04 AM, Deepak Goel  wrote:
>
>>
>> Hey
>>
>> Namaskara~Nalama~Guten Tag~Bonjour
>>
>> I am a newbie to Machine Learning (MLIB and other libraries on Spark)
>>
>> Which would be the best book to learn up?
>>
>> Thanks
>> Deepak
>>--
>> Keigu
>>
>> Deepak
>> 73500 12833
>> www.simtree.net, dee...@simtree.net
>> deic...@gmail.com
>>
>> LinkedIn: www.linkedin.com/in/deicool
>> Skype: thumsupdeicool
>> Google talk: deicool
>> Blog: http://loveandfearless.wordpress.com
>> Facebook: http://www.facebook.com/deicool
>>
>> "Contribute to the world, environment and more :
>> http://www.gridrepublic.org
>> "
>>
>
>

Re: Book for Machine Learning (MLIB and other libraries on Spark)

2016-06-11 Thread Ted Yu 
https://www.amazon.com/Machine-Learning-Spark-Powerful-Algorithms/dp/1783288515/ref=sr_1_1?ie=UTF8=1465657706=8-1=spark+mllib

https://www.amazon.com/Spark-Practical-Machine-Learning-Chinese/dp/7302420424/ref=sr_1_3?ie=UTF8=1465657706=8-3=spark+mllib

https://www.amazon.com/Advanced-Analytics-Spark-Patterns-Learning/dp/1491912766/ref=sr_1_2?ie=UTF8=1465657706=8-2=spark+mllib


On Sat, Jun 11, 2016 at 8:04 AM, Deepak Goel  wrote:

>
> Hey
>
> Namaskara~Nalama~Guten Tag~Bonjour
>
> I am a newbie to Machine Learning (MLIB and other libraries on Spark)
>
> Which would be the best book to learn up?
>
> Thanks
> Deepak
>--
> Keigu
>
> Deepak
> 73500 12833
> www.simtree.net, dee...@simtree.net
> deic...@gmail.com
>
> LinkedIn: www.linkedin.com/in/deicool
> Skype: thumsupdeicool
> Google talk: deicool
> Blog: http://loveandfearless.wordpress.com
> Facebook: http://www.facebook.com/deicool
>
> "Contribute to the world, environment and more :
> http://www.gridrepublic.org
> "
>

Book for Machine Learning (MLIB and other libraries on Spark)

2016-06-11 Thread Deepak Goel 
Hey

Namaskara~Nalama~Guten Tag~Bonjour

I am a newbie to Machine Learning (MLIB and other libraries on Spark)

Which would be the best book to learn up?

Thanks
Deepak
   --
Keigu

Deepak
73500 12833
www.simtree.net, dee...@simtree.net
deic...@gmail.com

LinkedIn: www.linkedin.com/in/deicool
Skype: thumsupdeicool
Google talk: deicool
Blog: http://loveandfearless.wordpress.com
Facebook: http://www.facebook.com/deicool

"Contribute to the world, environment and more : http://www.gridrepublic.org
"