NOVEMBER 27, 2024
While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. Create dbt models in dbt Cloud.
ODSC - Open Data Science
MARCH 12, 2025
AI engineering extended this by integrating AI systems more deeply into software engineering pipelines, making it a crucial field as AI applications became more sophisticated and embedded in real-world systems. Takeaway: The industrys focus has shifted from building models to making them robust, scalable, and maintainable.
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The MLOps Blog
SEPTEMBER 7, 2023
Data Scientists and ML Engineers typically write lots and lots of code. From writing code for doing exploratory analysis, experimentation code for modeling, ETLs for creating training datasets, Airflow (or similar) code to generate DAGs, REST APIs, streaming jobs, monitoring jobs, etc. Related post MLOps Is an Extension of DevOps.
ODSC - Open Data Science
OCTOBER 9, 2024
The rapid evolution of AI is transforming nearly every industry/domain, and software engineering is no exception. But how so with software engineering you may ask? These technologies are helping engineers accelerate development, improve software quality, and streamline processes, just to name a few.
AWS Machine Learning Blog
FEBRUARY 2, 2024
The embeddings are captured in Amazon Simple Storage Service (Amazon S3) via Amazon Kinesis Data Firehose , and we run a combination of AWS Glue extract, transform, and load (ETL) jobs and Jupyter notebooks to perform the embedding analysis. Set the parameters for the ETL job as follows and run the job: Set --job_type to BASELINE.
AWS Machine Learning Blog
JUNE 18, 2024
In this solution, we leverage the reasoning and coding abilities of LLMs for creating reusable Extract, Transform, Load (ETL), which transforms sensor data files that do not conform to a universal standard to be stored together for downstream calibration and analysis.
Marktechpost
JULY 5, 2024
It covers advanced topics, including scikit-learn for machine learning, statistical modeling, software engineering practices, and data engineering with ETL and NLP pipelines. The program culminates in a capstone project where learners apply their skills to solve a real-world data science challenge.
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