ODSC - Open Data Science

JULY 19, 2023

A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team. For the customer, this helps them reduce the time it takes to bootstrap a new data science project and get it to production.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

DataRobot Blog

SEPTEMBER 6, 2022

How do you drive collaboration across teams and achieve business value with data science projects? With AI projects in pockets across the business, data scientists and business leaders must align to inject artificial intelligence into an organization. Data Analysis Must Include Business Value.

Data Scientist 52

Data Scientist Data Drift Machine Learning Data Science 52

DataRobot Blog

DECEMBER 15, 2022

By simplifying Time Series Forecasting models and accelerating the AI lifecycle, DataRobot can centralize collaboration across the business—especially data science and IT teams—and maximize ROI. Prepare your data for Time Series Forecasting. Perform exploratory data analysis.

Machine Learning 81

Machine Learning AI AI Data Drift 81

The MLOps Blog

MARCH 20, 2023

Failure to consider the severity of these problems can lead to issues like degraded model accuracy, data drift, security issues, and data inconsistencies. Data retrieval: Having several dataset versions requires machine learning practitioners to know which dataset versions correspond to a certain model performance outcome.

ML 59

ML Data Drift Machine Learning Algorithm 59

Heartbeat

MARCH 21, 2023

There are several techniques used for model monitoring with time series data, including: Data Drift Detection: This involves monitoring the distribution of the input data over time to detect any changes that may impact the model’s performance. You can learn more about Comet here. You can get the full code here.

Machine Learning 59

Machine Learning Data Drift Data Scientist Data Analysis 59

Snorkel AI

MAY 12, 2023

Three experts from Capital One ’s data science team spoke as a panel at our Future of Data-Centric AI conference in 2022. Please welcome to the stage, Senior Director of Applied ML and Research, Bayan Bruss; Director of Data Science, Erin Babinski; and Head of Data and Machine Learning, Kishore Mosaliganti.

Machine Learning 52

Machine Learning Data Scientist Data Science ML 52

Snorkel AI

MAY 12, 2023

Three experts from Capital One ’s data science team spoke as a panel at our Future of Data-Centric AI conference in 2022. Please welcome to the stage, Senior Director of Applied ML and Research, Bayan Bruss; Director of Data Science, Erin Babinski; and Head of Data and Machine Learning, Kishore Mosaliganti.

Machine Learning 52

Machine Learning Data Scientist Data Science ML 52

AWS Machine Learning Blog

SEPTEMBER 21, 2023

This workflow will be foundational to our unstructured data-based machine learning applications as it will enable us to minimize human labeling effort, deliver strong model performance quickly, and adapt to data drift.” – Jon Nelson, Senior Manager of Data Science and Machine Learning at United Airlines.

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The MLOps Blog

MAY 9, 2023

Data validation This step collects the transformed data as input and, through a series of tests and validators, ensures that it meets the criteria for the next component. It checks the data for quality issues and detects outliers and anomalies. Kedro Kedro is a Python library for building modular data science pipelines.

ML 98

ML Machine Learning Metadata Data Science 98

Topbots

JUNE 29, 2023

However, as of now, unleashing the full potential of organisational data is often a privilege of a handful of data scientists and analysts. Most employees don’t master the conventional data science toolkit (SQL, Python, R etc.). Adaptability over time To use Text2SQL in a durable way, you need to adapt to data drift, i.

Auto-complete 52

Auto-complete Algorithm Data Scientist Auto-classification 52