Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022.

Data Quality 52

Data Quality Automation Data Scientist ML 52

Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022.

Data Quality 52

Data Quality Automation Data Scientist ML 52

Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022.

Data Quality 52

Data Quality Automation Data Scientist ML 52

AWS Machine Learning Blog

AUGUST 29, 2023

This architecture design represents a multi-account strategy where ML models are built, trained, and registered in a central model registry within a data science development account (which has more controls than a typical application development account). The data scientist can review and approve the new version of the model independently.

Data Scientist 91

Data Scientist Data Quality Python ML 91

AWS Machine Learning Blog

APRIL 26, 2023

Ensuring data quality, governance, and security may slow down or stall ML projects. The second is by using SageMaker to help data scientists and ML engineers build, train, and deploy custom ML models. MLOps engineering – Focuses on automating the DevOps pipelines for operationalizing the ML use case.

ML 114

ML Machine Learning Data Science Data Drift 114

AWS Machine Learning Blog

APRIL 21, 2023

See the following code: # Configure the Data Quality Baseline Job # Configure the transient compute environment check_job_config = CheckJobConfig( role=role_arn, instance_count=1, instance_type="ml.c5.xlarge", These are key files calculated from raw data used as a baseline.

Data Drift 98

Data Drift Metadata Data Quality ML 98

DataRobot Blog

FEBRUARY 11, 2022

These agents apply the concept familiar in the DevOps world—to run models in their preferred environments while monitoring all models centrally. DataRobot’s MLOps product offers a host of features designed to transform organizations’ user experience, firstly, through its model-monitoring agents. Governance and Trust.

Data Drift 52

Data Drift Machine Learning DevOps Data Scientist 52

Marktechpost

JULY 17, 2023

The advantages of using synthetic data include easing restrictions when using private or controlled data, adjusting the data requirements to specific circumstances that cannot be met with accurate data, and producing datasets for DevOps teams to use for software testing and quality assurance. Edgecase.ai

Machine Learning 52

Machine Learning Data Scientist Computer Vision Deep Learning 52

Pickl AI

APRIL 27, 2023

In addition to the conventional career choices, Data Science proficiency is gaining popularity. Since 2012, there has been a 650% rise in the demand for skilled and qualified data professionals. As a Data Scientist, the job opportunities are not limited to IT. This percentage is going to surge in the years to come.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Python 52

The MLOps Blog

APRIL 17, 2023

As an MLOps engineer on your team, you are often tasked with improving the workflow of your data scientists by adding capabilities to your ML platform or by building standalone tools for them to use. And since you are reading this article, the data scientists you support have probably reached out for help.

Metadata 52

Metadata Data Scientist Explainability ML 52

AWS Machine Learning Blog

FEBRUARY 28, 2023

If you want to add rules to monitor your data pipeline’s quality over time, you can add a step for AWS Glue Data Quality. And if you want to add more bespoke integrations, Step Functions lets you scale out to handle as much data or as little data as you need in parallel and only pay for what you use.

ML 91

ML Machine Learning Categorization NLP 91

The MLOps Blog

AUGUST 3, 2023

Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton. To a junior data scientist, it doesn’t matter if you’re using Airflow, Prefect , Dexter.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

The MLOps Blog

MAY 9, 2023

The platform typically includes components for the ML ecosystem like data management, feature stores, experiment trackers, a model registry, a testing environment, model serving, and model management. Data validation (writing tests to check for data quality). Data preprocessing.

ML 98

ML Machine Learning Metadata Data Science 98

The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

Pickl AI

MAY 15, 2024

This guide unlocks the path from Data Analyst to Data Scientist Architect. Data Quality and Standardization The adage “garbage in, garbage out” holds true. Inconsistent data formats, missing values, and data bias can significantly impact the success of large-scale Data Science projects.

Data Scientist 52

Data Scientist Data Science Machine Learning Data Quality 52