Cloudera

FEBRUARY 16, 2022

Support for multiple sessions within a project allows data scientists, engineers and operations teams to work independently alongside each other on experimentation, pipeline development, deployment and monitoring activities in parallel. To learn more about CML, head over to [link] or connect with us directly.

Machine Learning 82

Machine Learning Modeling Metadata Recreation/Entertainment 82

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.

Cost-Benefit 96

Cost-Benefit Modeling Manufacturing Interactive 96

Ontotext

NOVEMBER 6, 2019

At the same time, the community there is of users can share the best practices, enabling the cross-pollination of the most successful and most fruitful results of their experimentation. It also enables Ontotext to develop specific functionality as plugins without having to fiddle with the core functionality of the database. The Plugins.

Experimentation 45

Experimentation Deep Learning Software Modeling 45

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. Automated development: With AutoAI , beginners can quickly get started and more advanced data scientists can accelerate experimentation in AI development.

Machine Learning 79

Machine Learning Manufacturing Cost-Benefit Deep Learning 79

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. Metis Machine — Enterprise-scale Machine Learning and Deep Learning deployment and automation platform for rapid deployment of models into existing infrastructure and applications. DataOps is a hot topic in 2021.

Testing 307

Testing Machine Learning Consulting Data Quality 307

Domino Data Lab

FEBRUARY 12, 2020

this post on the Ray project blog ?. for reinforcement learning (RL), ? for model serving (experimental), are implemented with Ray internally for its scalable, distributed computing and state management benefits, while providing a domain-specific API for the purposes they serve. Ray: Scaling Python Applications. asyncio ?,

Experimentation 137

Experimentation Modeling Data Science Management 137

CDW Research Hub

AUGUST 21, 2019

Finally, perhaps the biggest obstacle faced when adopting an AI project is the time it takes to configure the server, prepare the data, build and train the model, and deploy and infer for deep learning. The kit helps facilitate clients’ AI adoption journey from experimentation to production.

Strategy 45

Strategy Deep Learning Machine Learning Experimentation 45

Domino Data Lab

MAY 8, 2019

Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. 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

Domino Data Lab

OCTOBER 14, 2020

Experimentation and collaboration are built into the core of the platform. We needed an “evolvable architecture” which would work with the next deep learning framework or compute platform. This ability enhances the efficiency of operational management and optimizes the cost of experimentation. Why Petastorm?

Experimentation 99

Experimentation Modeling Deep Learning Testing 99

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. Like this blog, it will be particularly relevant for those who are in digital analytics and digital marketing. Intro to Machine Learning. Machine Learning.

Marketing 136

Marketing Analytics Machine Learning Strategy 136