O'Reilly on Data

APRIL 19, 2021

We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. First, 82% of the respondents are using supervised learning, and 67% are using deep learning. 58% claimed to be using unsupervised learning. Bottlenecks to AI adoption.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

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. Example: A student is struggling with a complex math concept.

Cost-Benefit 88

Cost-Benefit Modeling Manufacturing Interactive 88

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. Introduction.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

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. Visual modeling: Combine visual data science with open source libraries and notebook-based interfaces on a unified data and AI studio.

Machine Learning 77

Machine Learning Manufacturing Cost-Benefit Deep Learning 77

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. Polyaxon — An open-source platform for reproducible machine learning at scale. Kubeflow — The Machine Learning Toolkit for Kubernetes. Meta-Orchestration .

Testing 307

Testing Machine Learning Consulting Data Quality 307

Domino Data Lab

MAY 8, 2019

On the other hand, as Lipton emphasized, while the tooling produces interesting visualizations, visualizations do not imply interpretation. ML model interpretability and data visualization. From my experiences leading data teams, when a business is facing difficult challenges, data visualizations can help or hurt.

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. It used deep learning to build an automated question answering system and a knowledge base based on that information.

Management 110

Management Machine Learning Experimentation Metrics 110

O'Reilly on Data

SEPTEMBER 11, 2019

Our call for speakers for Strata NY 2019 solicited contributions on the themes of data science and ML; data engineering and architecture; streaming and the Internet of Things (IoT); business analytics and data visualization; and automation, security, and data privacy. Deep learning,” for example, fell year over year to No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Domino Data Lab

OCTOBER 14, 2020

We’ve developed a model-driven software platform, called Climate FieldView , that captures, visualizes, and analyzes a vast array of data for farmers and provides new insight and personalized recommendations to maximize crop yield. Experimentation and collaboration are built into the core of the platform. Hyperparameter Tuning.

Experimentation 99

Experimentation Modeling Deep Learning Testing 99