AWS Machine Learning Blog

FEBRUARY 28, 2024

About the Authors Sanjeeb Panda is a Data and ML engineer at Amazon. With the background in AI/ML, Data Science and Big Data, Sanjeeb design and develop innovative data and ML solutions that solve complex technical challenges and achieve strategic goals for global 3P sellers managing their businesses on Amazon.

Metadata 129

Metadata LLM Generative AI NLP 129

The MLOps Blog

JUNE 27, 2023

Model governance and compliance : They should address model governance and compliance requirements, so you can implement ethical considerations, privacy safeguards, and regulatory compliance into your ML solutions. This includes features for model explainability, fairness assessment, privacy preservation, and compliance tracking.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

OCTOBER 2, 2024

Model transparency – Although achieving full transparency in generative AI models remains challenging, organizations can take several steps to enhance model transparency and explainability: Provide model cards on the model’s intended use, performance, capabilities, and potential biases.

Generative AI 117

Generative AI Data Ingestion AI AI 117

AWS Machine Learning Blog

JUNE 3, 2024

To learn more about how SageMaker Canvas uses training and validation datasets, see Evaluating Your Model’s Performance in Amazon SageMaker Canvas and SHAP Baselines for Explainability. About the Authors Rushabh Lokhande is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice.

Categorization 112

Categorization Generative AI Auto-complete Auto-classification 112

Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms.

Data Scientist 52

Data Scientist Machine Learning Big Data Algorithm 52

AWS Machine Learning Blog

APRIL 11, 2023

We explain the process and network flow, and how to easily scale this architecture to multiple accounts and Amazon SageMaker domains. Steps 1–4 are covered in more detail in Part 2 of this series, where we explain how the custom Lambda authorizer works and takes care of the authorization process in the access API Gateway.

IDP 83

IDP Explainability Big Data ML 83

AWS Machine Learning Blog

FEBRUARY 7, 2025

This post, part of the Governing the ML lifecycle at scale series ( Part 1 , Part 2 , Part 3 ), explains how to set up and govern a multi-account ML platform that addresses these challenges. Usually, there is one lead data scientist for a data science group in a business unit, such as marketing.

ML 63

ML Data Scientist ML Engineer Data Science 63

Pickl AI

JULY 14, 2023

Big Data and Deep Learning (2010s-2020s): The availability of massive amounts of data and increased computational power led to the rise of Big Data analytics. Deep Learning, a subfield of ML, gained attention with the development of deep neural networks.

Neural Network 52

Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

Mlearning.ai

FEBRUARY 9, 2023

I started working in Data Science right after graduating with an MS degree in Electrical and Computer Engineering from the University of California, Los Angeles (UCLA). You could be working entirely on data analytics under a Data Scientist job title. Model explainability is an important skill for a Data Scientist’s job.

Data Scientist 52

Data Scientist Data Science ML Machine Learning 52

Flipboard

MARCH 7, 2023

Because of this difference, there are some specifics of how you create and manage virtual environments in Studio notebooks , for example usage of Conda environments or persistence of ML development environments between kernel restarts. He develops and codes cloud native solutions with a focus on big data, analytics, and data engineering.

Python 123

Python Data Science Data Scientist ML 123

AWS Machine Learning Blog

NOVEMBER 9, 2023

This collaboration ensures that your MLOps platform can adapt to evolving business needs and accelerates the adoption of ML across teams. Machine Learning Engineer with AWS Professional Services. She is passionate about developing, deploying, and explaining AI/ ML solutions across various domains. Sunita Koppar is a Sr.

Data Drift 119

Data Drift Auto-complete ML Automation 119

The MLOps Blog

AUGUST 11, 2023

At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. But some of these queries are still recurrent and haven’t been explained well. In the case of ride-hailing apps, each activity outcome contributes to completing the ride-hailing process.

ML 52

ML Machine Learning Data Ingestion Deep Learning 52

AWS Machine Learning Blog

NOVEMBER 13, 2024

With the unification of SageMaker Model Cards and SageMaker Model Registry, architects, data scientists, ML engineers, or platform engineers (depending on the organization’s hierarchy) can now seamlessly register ML model versions early in the development lifecycle, including essential business details and technical metadata.

Metadata 104

Metadata ML Software Engineer Machine Learning 104