Artificial Intelligence, Data science and Manufacturing

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data science

Data science Analytics Unstructured data Artificial Intelligence

Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Data science

Data science Big data Analytics Mining

How to build a successful AI strategy

IBM Big Data Hub

DECEMBER 20, 2023

Artificial intelligence (AI) is a transformative force. The automation of tasks that traditionally relied on human intelligence has far-reaching implications, creating new opportunities for innovation and enabling businesses to reinvent their operations. What is an AI strategy?

Artificial Intelligence

Artificial Intelligence Customer Experience Cloud Government

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

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Great Data Scientists Don’t Just Think Outside the Box, They Redefine the Box

Bill Schmarzo - Dell EMC

FEBRUARY 28, 2018

It’s a data scientist’s most important concept, because “might” gives the data scientist the license to explore, be wrong, learn and try again. “It It Can’t Be Done” Is Not a Data Scientist Term. Figure 5: Using RNN’s to Identify Shapes and Patterns Buried in the Telemetry Data. Michael holds U.S.

Data science

Data science Artificial Intelligence Big data Cloud

Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Big Data Hub

DECEMBER 19, 2023

Anomalies are not inherently bad, but being aware of them, and having data to put them in context, is integral to understanding and protecting your business. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

Unstructured data

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How we used generative AI to run a generative AI hackathon

Collibra

AUGUST 23, 2023

As the data intelligence company, we’ve long anticipated broad adoption of AI, and Collibrians with data science and machine learning expertise have been working diligently on ways to apply AI/ML. She said some of the first results were more relevant for a manufacturing hackathon than a software hackathon.

Communications

Communications Data science Marketing Artificial Intelligence

Generative AI use cases for the enterprise

IBM Big Data Hub

FEBRUARY 13, 2024

Generative AI ( artificial intelligence ) promises a similar leap in productivity and the emergence of new modes of working and creating. Key considerations: Tech stack: Ensure your existing technology infrastructure can handle the demands of AI models and data processing.

Artificial Intelligence

Artificial Intelligence Marketing Sales Communications

Getting ready for artificial general intelligence with examples

IBM Big Data Hub

APRIL 18, 2024

While AGI remains theoretical, organizations can take proactive steps to prepare for its arrival by building a robust data infrastructure and fostering a collaborative environment where humans and AI work together seamlessly. Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move.

Artificial Intelligence

Artificial Intelligence Marketing e-Delivery Manufacturing

Artificial Intelligence: 6 Step Solution Decomposition Process

Bill Schmarzo - Dell EMC

MARCH 5, 2018

The conversation is simple because the objective is simple: How do I become more effective at leveraging (big) data and analytics (artificial intelligence) to power my business? Artificial Intelligence Solution Decomposition Process. Figure 1: The Evolution of AI, ML and DL (Source: Nvidia ).

Artificial Intelligence

Artificial Intelligence Analytics Big data Mining

10 everyday machine learning use cases

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029.

Marketing

Marketing Data science e-Discovery Artificial Intelligence

Artificial Intelligence: 6 Step Solution Decomposition Process

Bill Schmarzo - Dell EMC

MARCH 5, 2018

The conversation is simple because the objective is simple: How do I become more effective at leveraging (big) data and analytics (artificial intelligence) to power my business? Artificial Intelligence Solution Decomposition Process. Figure 1: The Evolution of AI, ML and DL (Source: Nvidia ).

Artificial Intelligence

Artificial Intelligence Analytics Mining Big data

How to choose the best AI platform

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. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Data science

Data science Manufacturing Artificial Intelligence Retail

#ModernDataMasters: Martin Squires, The Analysis Foundry

Reltio

JULY 2, 2019

Martin Squires is a leader with extensive experience in customer insight, marketing analytics & data science. Selected for the last 5 years as a member of the Data IQ Data 100 , Martin has considerable experience helping organisations drive value from building a deeper understanding of their customers.

Analytics

Analytics Insurance Artificial Intelligence Data science

#ModernDataMasters: Michele Chambers, AWS

Reltio

JULY 31, 2019

For me, modern data management is about technology giving you the power to change the way your business is moving and with the same fluidity. Advanced analytics, or artificial intelligence (AI), still has a ways to go. People don’t really understand it yet in terms of its application to business.

Analytics

Analytics Blockchain Cloud Artificial Intelligence

Part 1: OMG! Not another digital transformation article! Is it about understanding the business drivers?

ARMA International

SEPTEMBER 13, 2021

The nomenclature can extend to include Data as a Service (DaaS), Content as a Service (CaaS), and Managed Content as a Service (MCaaS) to deliver digital interaction experiences to customers. More recent technology trends include Blockchain as a Service (BaaS) and Artificial Intelligence as a Service (AIaaS).

Digital transformation

Digital transformation Blockchain IT Computer and Electronics

How foundation models and data stores unlock the business potential of generative AI

IBM Big Data Hub

AUGUST 1, 2023

Foundation models: The driving force behind generative AI Also known as a transformer, a foundation model is an AI algorithm trained on vast amounts of broad data. The term “foundation model” was coined by the Stanford Institute for Human-Centered Artificial Intelligence in 2021.

Artificial Intelligence

Artificial Intelligence Marketing Unstructured data Manufacturing

Foundational models at the edge

IBM Big Data Hub

SEPTEMBER 20, 2023

Foundational models (FMs) are marking the beginning of a new era in machine learning (ML) and artificial intelligence (AI) , which is leading to faster development of AI that can be adapted to a wide range of downstream tasks and fine-tuned for an array of applications.

Cloud

Cloud Data science Artificial Intelligence Analytics

Information Management Today

Data science vs data analytics: Unpacking the differences

Data science vs. machine learning: What’s the difference?

Webinars

Trending Sources

How to build a successful AI strategy

Webinars

Great Data Scientists Don’t Just Think Outside the Box, They Redefine the Box

Anomaly detection in machine learning: Finding outliers for optimization of business functions

How we used generative AI to run a generative AI hackathon

Generative AI use cases for the enterprise

Getting ready for artificial general intelligence with examples

Artificial Intelligence: 6 Step Solution Decomposition Process

10 everyday machine learning use cases

Artificial Intelligence: 6 Step Solution Decomposition Process

How to choose the best AI platform

#ModernDataMasters: Martin Squires, The Analysis Foundry

#ModernDataMasters: Michele Chambers, AWS

Part 1: OMG! Not another digital transformation article! Is it about understanding the business drivers?

How foundation models and data stores unlock the business potential of generative AI

Foundational models at the edge

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