APIs Banking Engineering Scripts 
AWS Machine Learning
FEBRUARY 13, 2024
Let’s demystify this using the following personas and a real-world analogy: Data and ML engineers (owners and producers) – They lay the groundwork by feeding data into the feature store Data scientists (consumers) – They extract and utilize this data to craft their models Data engineers serve as architects sketching the initial blueprint.
AWS Machine Learning
MARCH 21, 2023
It contains over 300 built-in data transformation steps to aid with feature engineering, normalization, and cleansing to transform your data without having to write any code. For this post, we use the bank-full.csv data from the University of California Irving Machine Learning Repository to demonstrate these functionalities.
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AWS Machine Learning
OCTOBER 25, 2022
Model weights are available via scripts in the GitHub repository , and the MSAs are hosted by the Registry of Open Data on AWS (RODA). We use aws-do-eks , an open-source project that provides a large collection of easy-to-use and configurable scripts and tools to enable you to provision EKS clusters and run your inference.
AWS Machine Learning
DECEMBER 29, 2022
Users can also interact with data with ODBC, JDBC, or the Amazon Redshift Data API. This blog focuses on the Rstudio on Amazon SageMaker language, with business analysts, data engineers, data scientists, and all developers that use the R Language and Amazon Redshift, as the target audience. Prerequisites.
AWS Machine Learning
AUGUST 4, 2022
This is a guest post by Viktor Enrico Jeney, Senior Machine Learning Engineer at Adspert. The repricing ML model is a Scikit-Learn Random Forest implementation in SageMaker Script Mode, which is trained using data available in the S3 bucket (the analytics layer). This may be different to the partitioning used on the stage layer.
AWS Machine Learning
JULY 29, 2022
The data scientists in this team use Amazon SageMaker to build and train a credit risk prediction model using the shared credit risk data product from the consumer banking LoB. Now that you have a subset of the data as a dataframe, you can start exploring the data and see what feature engineering updates are needed for model training.
AWS Machine Learning
AUGUST 14, 2023
Prompt engineering for zero-shot and few-shot NLP tasks on BLOOM models Prompt engineering deals with creating high-quality prompts to guide the model towards the desired responses. Prompt engineering can greatly improve the performance of zero-shot and few-shot learning models. He is currently a Senior Adviser of CITIC CLSA.
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