Ninad Kulkarni

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since Aug 31, 2007
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Recent posts by Ninad Kulkarni

Noah Gift wrote:In the example shown there are a couple of "pragmatic" approaches that could tried first, ie. in the spirit of using the highest level tools first. I would approach the problem like this:

Step 1:  Spin up an AWS Sagemaker Instance
Step 2:  Create a Jupyter Notebook
Step 3:  Clean up the data and do some clustering and see if there are some clusters that create types of transactions and plot (with on axis being transaction size)
Step 4:  Add the labels to the original data set and predict which cluster something could be assigned to and deploy via Sagemaker (to either production or other team members via about 1 line of code)

Off the top of my head a workflow like this could be a rapid way to approach the problem

Thanks a lot Noah

Tim Moores wrote:What is or does a "Acquiring Card Payment System"? What does it have to do with reward points?


Acquirer passes Merchant transaction to issuer bank who issue card to card holder. Reward point gets calculated on amount of transaction done on merchant terminal for specific scheme or program which can be loyalty program.

Tim Moores wrote:What is or does a "Acquiring Card Payment System"? What does it have to do with reward points?


Acquirer passes Merchant transaction to issuer bank who issue card to card holder. Reward point gets calculated on amount of transaction done on merchant terminal for specific scheme or program which can be loyalty program.

Noah Gift wrote:One particular way to handle things in a pragmatic manner would be to leverage "by the book" recommendations from a Cloud provider:  AWS, Azure, GCP.  Use their recommended tools and workflows to create a cloud-native architecture that can work with an existing banking architecture.  A good example would be to read through some of the AWS whitepapers:  https://aws.amazon.com/whitepapers/, then apply that thinking to creating AI solutions for banking.


Thanks Noah for information

Tim Moores wrote:What is "core banking"?


Core banking is where data is coming from all sources like POS transaction / ATM transaction / Internet Banking / Mobile Transaction etc. We will have huge volume of transactions and processing large data on Big Data using Cloud
Hi Noah,

How Pragmatic AI will help to create AI solution using cloud for Energy sector.

Best Regards,
Ninad Kulkarni
Hi Noah,

How Pragmatic AI will help us to perform machine learning for core banking on cloud for large volume of data.

Best Regards,
Ninad Kulkarni
Hi Noah,

How Pragmatic AI book will help to build Artificial Intelligence for Acquiring Card Payment System. This is with respect to Payment Systems in Financial Transactions. Can we build a prediction system which will tell us which type of transactions will give us more rewards points.

Best Regards,
Ninad Kulkarni
How we can migrate easily to Neo4j from exisitng NoSQL database?
3 years ago
What are the advantages of Neo4j interms of Performance, Scalability and Availabilty.?
3 years ago
If you write table 1 and then table 2 into single flat file then its possible without using Spring batch but if you want to write simultaneously into single flat file then you can choose parallel processing.
Let see what other will mention here
3 years ago
I think this is related to installation
3 years ago
What are advantages of Lambada Expression introduced in Java 8?

Which scenario shall we use Lambada Expression?
3 years ago