Domino Data Lab

MARCH 11, 2021

Here are several key considerations you should take into account when selecting a machine learning framework for your project. When you start your search for a machine learning framework, ask these three questions: Will you use the framework for deep learning or classic machine learning algorithms?

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

bridgei2i

OCTOBER 7, 2020

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. The way ahead for insurers.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

datapine

NOVEMBER 19, 2019

Exciting and futuristic, the concept of computer vision is based on computing devices or programs gaining the ability to extract detailed information from visual images. Visual analytics: Around three million images are uploaded to social media every single day. Artificial Intelligence (AI). Connected Retail.

Technology 279

Technology Internet of Things IT IoT 279

AWS Big Data

MAY 16, 2024

However, visualizing and analyzing large-scale geospatial data presents a formidable challenge due to the sheer volume and intricacy of information. This often overwhelms traditional visualization tools and methods. Figure 1 – Map built with CARTO Builder and the native support to visualize H3 indexes What are spatial indexes?

Data Warehouse 108

Data Warehouse Visualization Cost-Benefit Optimization 108

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. However, these solutions are independent components of the data toolchain that collect, store, transform, visualize, and govern the data running through the pipeline.

Testing 300

Testing Machine Learning Consulting Data Quality 300

Cloudera

FEBRUARY 4, 2019

It is a key capability that will address the needs of our combined customer base in areas of real-time streaming architectures and Internet-of-Things (IoT). It meets the challenges faced with data-in-motion, such as real-time stream processing, data provenance, and data ingestion from IoT devices and other streaming sources.

IoT 73

IoT Prescriptive Analytics Digital Transformation Internet of Things 73

CIO Business Intelligence

APRIL 12, 2022

A security infrastructure can provide a foundation which captures audio and video data, and data from IoT devices, which the computer vision system then combines and analyzes, producing insights that can be used to positively impact safety, the customer experience, operational efficiencies, sustainability and revenue generation.

IT 72

IT Cost-Benefit IoT Machine Learning 72

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

BizAcuity

MARCH 31, 2022

Integrating IoT and route optimization are two other important places that use AI. For accurate predictions, companies now use various data models, machine and deep learning techniques to continuously improve and refine the quality of the outcome. AI in Healthcare.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Alation

APRIL 14, 2022

Visual Profiling. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. An inference algorithm that informs the analyst with a ranked set of suggestions about the transformation. Parametrization. A technique to automate changes in iterative passes. Scheduling.

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