Domino Data Lab

MARCH 11, 2021

In this article, we’ll show key considerations for selecting the right machine learning framework for your project and briefly review four popular ML frameworks. Here are several key considerations you should take into account when selecting a machine learning framework for your project. Parameter Optimization.

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

IBM Big Data Hub

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. It signifies a shift in human-digital interaction, offering enterprises innovative ways to engage with their audience, optimize operations, and further personalize their customer experience. billion by 2030.

Enterprise 96

Enterprise Interactive Data-driven Key Performance Indicator 96

bridgei2i

OCTOBER 7, 2020

Importance of capturing market data for optimized pricing models. The automated process can then be used to parse data sources like structured and unstructured data sources such as – IoT data, claims data, physical proofs, social data, life health data and in a variety of formats such as textual, visual, sensor-based and electronic etc.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

Cloudera

SEPTEMBER 11, 2020

The need to start better leveraging external data, working with broader data sets inclusive of incremental ‘demand signals,’ is no longer a ‘nice to have’ in order to improve forecast accuracy and inventory optimization. Automation opportunities. Companies are also shifting their technology investments.

Manufacturing 95

Manufacturing Forecasting Digital Transformation Sales 95

Cloudera

SEPTEMBER 12, 2018

AbbVie’s platform uses analytics and machine learning, including natural language processing, deep learning, and unsupervised learning, to proactively identify issues and opportunities. Brian Buntz , Content Director, Iot Institute, Informa, @brian_buntz. Mike Barlow , Managing Partner, Cumulus Partners.

Machine Learning 46

Machine Learning Big Data Data Science Data Warehouse 46

Insight

MARCH 5, 2019

Internet of Thing (AWS IoT) Are you looking to transition into the field of machine learning in Silicon Valley, New York, or Toronto? Apply for the upcoming June session today ( Deadline is March 25th for SV and NYC ) or learn more about the Artificial Intelligence program at Insight!

Machine Learning 71

Machine Learning Internet of Things Recreation/Entertainment IoT 71

AWS Big Data

MAY 16, 2024

Because of this, many organizations are utilizing them as a support geography, aggregating their data to these grids to optimize both their storage and analysis. To learn more details about their benefits, see Introduction to Spatial Indexes. To learn more, visit CARTO.

Data Warehouse 108

Data Warehouse Visualization Cost-Benefit Optimization 108

DataKitchen

APRIL 13, 2021

Observe, optimize, and scale enterprise data pipelines. . Metis Machine — Enterprise-scale Machine Learning and Deep Learning deployment and automation platform for rapid deployment of models into existing infrastructure and applications. Varada – Self-optimizing cloud data virtualization platform. . Data breaks.

Testing 300

Testing Machine Learning Consulting Data Quality 300

datapine

NOVEMBER 19, 2019

There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others. While IoT was a prominent feature of buzzwords 2019, the rapid advancement and adoption of the internet of things is a trend you cannot afford to ignore in 2020.

Technology 279

Technology Internet of Things IT IoT 279

AWS Big Data

OCTOBER 26, 2023

Some recent examples of performance optimizations driven by fleet telemetry include: String query optimizations – By analyzing how Amazon Redshift processed different data types in the Redshift fleet, we found that optimizing string-heavy queries would bring significant benefit to our customers’ workloads.

Data Warehouse 96

Data Warehouse Cost-Benefit Dashboards Optimization 96

Smart Data Collective

MAY 17, 2021

A critical component of smarter data-driven operations is commercial IoT or IIoT, which allows for consistent and instantaneous fleet tracking. The global IoT fleet management market is expected to reach $17.5 It can also be used to analyze driver behaviors to optimize fuel stops, personal breaks and more. billion in 2018.

Big Data 100

Big Data Cost-Benefit IoT Machine Learning 100

CIO Business Intelligence

APRIL 12, 2022

Computer vision is helping to reshape the transportation industry at every level from streamlining the passenger experience to preemptive fleet maintenance to fuel optimization. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use.

IT 72

IT Cost-Benefit IoT Machine Learning 72

BizAcuity

JUNE 16, 2022

Under this model, the strategy is to make use of both private (for highly confidential data) and public cloud infrastructure for cost and performance optimization. Edge computing comes as a boon for industries that depend on IoT like logistics and telecommunications. So as to cut latency and optimize the cloud storage system.

Data-driven 52

Data-driven IoT Data Processing Optimization 52

BizAcuity

MARCH 31, 2022

Marketers also have access to several AI softwares to save time and optimize their work at every step of the funnel. Integrating IoT and route optimization are two other important places that use AI. Predictive analytics, with the help of machine learning, keeps getting more accurate with the continuous inflow of data.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

IBM Big Data Hub

MAY 17, 2023

Additionally, DaaS has the potential to leverage smart technologies such as IoT, sensors, 5G, edge analytics and machine learning to improve the monitoring and visualization of assets operations. DaaS uses built-in deep learning models that learn by analyzing images and video streams for classification.

Data Collection 77

Data Collection Visualization Data-driven Unstructured Data 77

Alation

APRIL 14, 2022

They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. Governance influences how an organization’s objectives are set and achieved, how risk is monitored and addressed, and how performance is optimized.” It’s not a simple definition.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Domino Data Lab

MARCH 3, 2019

O’Reilly Media had an earlier survey about deep learning tools which showed the top three frameworks to be TensorFlow (61% of all respondents), Keras (25%), and PyTorch (20%)—and note that Keras in this case is likely used as an abstraction layer atop TensorFlow. The data types used in deep learning are interesting.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

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

CIO Business Intelligence

JANUARY 20, 2023

Though experts agree on the difficulty of deploying new platforms across an enterprise, there are options for optimizing the value of AI and analytics projects. [2] To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use.

Analytics 137

Analytics Key Performance Indicator Unstructured Data IoT 137