Showing posts with label Machine. Show all posts
Showing posts with label Machine. Show all posts

Saturday, 14 January 2017

Learning Numpy #2

Thursday, 12 January 2017

Learning Numpy #1


Numpy is a python library used for numerical calculations and this is better performant than pure python. In this notebook, I have shared some basics of Numpy and will share more in next few posts. I hope you find these useful.





Click Here for Next Tutorial ~

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Wednesday, 11 January 2017

My Learning Path for Machine Learning


I am a Python Lover guy so my way includes lots of Python points. If you dont know the basics of this wonderful language, start it from HERE else you can follow the links which I am going to share.

Learning ML is not only studying ML algorithms, it includes Basic Algebra, Statistics, Algorithms, Programming and lot more. But no need to afraid as such :-) we need to start from somewhere.....

This is my github repo, you can fork it and follow me with these 2 links --

Fork Fork
Follow - Follow @atulsingh0
I am still updating this list and welcome you to update this as well.



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Friday, 6 January 2017

10 minutes with pandas library

Thursday, 5 January 2017

Learning Pandas #5 - read & write data from file

Wednesday, 4 January 2017

Learning Pandas #4 - Hierarchical Indexing

Sunday, 1 January 2017

Learning Pandas #3 - Working on Summary & MissingData

Saturday, 31 December 2016

Learning Pandas - DataFrame #2

Friday, 30 December 2016

Learning Pandas - Series #1

Wednesday, 28 December 2016

Learning Graphlab - SFrame #2

In last post Learning Graphlab - SFrame #1, we have learn basics of SFrame, like how to create, add or delete the columns in SFrame. In this post, we will revise it once again and learn some advance features of SFrame. Have a good learnng !!!

You can view the Jupyter Notebook for the same HERE




Wednesday, 7 December 2016

Import the jobs from DS windows client #iLoveScripting


As we have discussed a script which can export the datastage jobs from your client system (http://bit.ly/2frNPKj) likewise we can write another one to import the jobs. Let's see how -

DsImportJobsClient.bat :

This Script read all the *.dsx job name from the specified Directory and Sub-Directory and import to the Specified project. It can also build (Only BUILD) the existing package created on Information Server Manager and send it to the specified location on client machine.

To use the build feature you need to make sure the package has been created with all the needed jobs, saved and closed. Only update to the selected job will be taken care automatically. To add/delete a job, you need to do manually.

Modify the Import.properties and ImportJobList.txt file and Go the .bat dir and then execute the importAndBuild.bat.




Import.properties :


ImportJobList.txt :


DsImportJobsClient.bat :





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Wednesday, 30 November 2016

Learning Graphlab - SFrame #1


Hoping you guys went through the last post (Lnk -> Getting Started with Graphlab), In this post we will do some handson SFrame datatype of Graphlab which is same as dataframe of pandas python library.

i. Reading the CSV file
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rdCSV

ii. save DataSet 
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iii. load DataSet
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iv. Check Total Rows and Columns
==
rowNum

v. Check Columns data type and Name
==
colTypes

vi. Add new column
==
addCol

vii. Delete column
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viii. Rename column
==
renameCol

ix. Column Swapping (location)
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Sunday, 27 November 2016

Getting Started with Graphlab - A Python library for Machine Learning


Before Starting with Graphlab, We have to configure our system with some basic tools such as Python, Jupyter Notebook etc. You can find 'How-To' on this link - http://bit.ly/2gvuG95

What is GraphLab ??
GraphLab Create is a Python library, backed by a C++ engine, for quickly building large-scale, high-performance data products. Some key features of GraphLab Create are:
  • Analyze terabyte scale data at interactive speeds, on your desktop.
  • A Single platform for tabular data, graphs, text, and images.
  • State of the art machine learning algorithms including deep learning, boosted trees, and factorization machines.
  • Run the same code on your laptop or in a distributed system, using a Hadoop Yarn or EC2 cluster.
  • Focus on tasks or machine learning with the flexible API.
  • Visualize data for exploration and production monitoring.
After the installation of Graphlab library we can use it as any python library.

Use Jupyter Notebook for starter, Open a Python notebook in Jupyter Notebook and execute below commands to see graphlab working -

 a. Importing Graphlab - 

=





b. Reading CSV file
This method will parse the input file and convert it into a SFrame variable

==


c. Getting Started with SFrame 

i. View content of SFrame variable sf

==


ii. View Head lines (top lines) 

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ii. View Tail lines (last lines)
 
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Sunday, 6 November 2016

Export the jobs from DS windows client



Datastage jobs Export/Import are occasional activity (Deployment time :-)) for a developer But it becomes very tedious if the job list are long or it's daily routine to export or import jobs.

So I have written a batch script (windows script) which we can execute from the Client Machine (where datastage clients are installed) and automate this process.



DSjobExportClient.bat :
Export Script read the job name from the file (ExportJobList.txt) and exports the jobName.dsx from the project to the export base location and maintain the folder structure specified in the ExportJobList.txt file. File "ExportJobList.txt" and “Export.properties” should be updated before running the export script.

Copy the above file on any location of your DS windows client machine and update the "ExportJobList.txt" and “Export.properties” files.
-    Export.properties
-    ExportJobList.txt
-    ExportJobs.bat   



Export.properties :


ExportJobList.txt :


DsExportJobsClient.bat :




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