Domino Data Lab

APRIL 7, 2019

A good NLP library will, for example, correctly transform free text sentences into structured features (like cost per hour and is diabetic ), that easily feed into a machine learning (ML) or deep learning (DL) pipeline (like predict monthly cost and classify high risk patients ). Image Credit: Parsa Ghaffari on the Raylien Blog.

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Scale the problem to handle complex data structures. BTW, videos for Rev2 are up: [link].

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

IBM Big Data Hub

APRIL 18, 2024

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. The AGI analyzes the data and identifies a rare genetic mutation linked to a specific disease.

Cost-Benefit 97

Cost-Benefit Modeling Manufacturing Interactive 97

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Machine learning model interpretability. back to the structure of the dataset.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

O'Reilly on Data

OCTOBER 19, 2021

It has far-reaching implications as to how such applications should be developed and by whom: ML applications are directly exposed to the constantly changing real world through data, whereas traditional software operates in a simplified, static, abstract world which is directly constructed by the developer. This approach is not novel.

IT 346

IT Testing Experimentation Software 346

DataRobot

DECEMBER 16, 2021

Take advantage of DataRobot’s wide range of options for experimentation. Use DataRobot’s AutoML and AutoTS to tackle various data science problems such as classification, forecasting, and regression. Not sure where to start with your massive trove of text data? More Value with Less Efforts.

Experimentation 98

Experimentation Unstructured Data Deep Learning Modeling 98

DataRobot Blog

MARCH 7, 2023

DataRobot on Azure accelerates the machine learning lifecycle with advanced capabilities for rapid experimentation across new data sources and multiple problem types. The capability to rapidly build an AI-powered organization with industry-specific solutions and expertise.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59