Rocket-Powered Data Science

JULY 6, 2021

The Edge-to-Cloud architectures are responding to the growth of IoT sensors and devices everywhere, whose deployments are boosted by 5G capabilities that are now helping to significantly reduce data-to-action latency. 7) Deep learning (DL) may not be “the one algorithm to dominate all others” after all.

Machine Learning 279

Machine Learning Data-driven Deep Learning IoT 279

datapine

NOVEMBER 19, 2019

An important part of artificial intelligence comprises machine learning, and more specifically deep learning – that trend promises more powerful and fast machine learning. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

Smart Data Collective

DECEMBER 1, 2022

As we look ahead to 2022, there are four key trends that organizations should be aware of when it comes to big data: cloud computing, artificial intelligence, automated streaming analytics, and edge computing. Each of these trends will continue to shape the way companies use data in the coming years.

Big Data 145

Big Data Internet of Things Data-driven Deep Learning 145

Cloudera

FEBRUARY 4, 2019

One of the most promising technology areas in this merger that already had a high growth potential and is poised for even more growth is the Data-in-Motion platform called Hortonworks DataFlow (HDF). CDF, as an end-to-end streaming data platform, emerges as a clear solution for managing data from the edge all the way to the enterprise.

IoT 73

IoT Prescriptive Analytics Internet of Things Digital Transformation 73

IBM Big Data Hub

APRIL 22, 2024

Our approach includes applying AI, Internet of Things (IoT), and advanced data and automation solutions to empower this transition. Generative AI refers to deep-learning models that can take raw data and “learn” to generate statistically probable outputs when prompted.

IoT 77

IoT Internet of Things Cost-Benefit Reporting 77

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. training data”) show the tangible outcomes.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

IBM Big Data Hub

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. Marketing and sales: Conversational AI has become an invaluable tool for data collection. It assists customers and gathers crucial customer data during interactions to convert potential customers into active ones.

Enterprise 95

Enterprise Interactive Data-driven Key Performance Indicator 95