Smart Data Collective

SEPTEMBER 23, 2020

While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data.

Data Lake 135

Data Lake Data Warehouse Unstructured Data Big Data 135

CIO Business Intelligence

JANUARY 24, 2024

It’s the culmination of a decade of work on deep learning AI. Deep learning AI: A rising workhorse Deep learning AI uses the same neural network architecture as generative AI, but can’t understand context, write poems or create drawings. You probably know that ChatGPT wasn’t built overnight.

Deep Learning 112

Deep Learning Unstructured Data Machine Learning Modeling 112

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. Before selecting a tool, you should first know your end goal – machine learning or deep learning.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

Smart Data Collective

JUNE 10, 2022

The average data scientist earns over $108,000 a year. The interdisciplinary field of data science involves using processes, algorithms, and systems to extract knowledge and insights from both structured and unstructured data and then applying the knowledge gained from that data across a wide range of applications.

Data Science 144

Data Science Machine Learning Statistics Business Intelligence 144

IBM Big Data Hub

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Deep Learning 56

Deep Learning Machine Learning Unstructured Data Modeling 56

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

CIO Business Intelligence

JANUARY 20, 2023

Look at Enterprise Infrastructure An IDC survey [1] of more than 2,000 business leaders found a growing realization that AI needs to reside on purpose-built infrastructure to be able to deliver real value. 2] Foundational considerations include compute power, memory architecture as well as data processing, storage, and security.

Analytics 137

Analytics Key Performance Indicator Unstructured Data Deep Learning 137

CIO Business Intelligence

AUGUST 11, 2023

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning.

Unstructured Data 142

Unstructured Data Machine Learning Data Science Data mining 142

IBM Big Data Hub

DECEMBER 5, 2023

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time.

Unstructured Data 90

Unstructured Data Cost-Benefit Machine Learning Experimentation 90

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

IBM Big Data Hub

JANUARY 10, 2024

Algorithms: Algorithms are the sets of rules AI systems use to process data and make decisions. The category of AI algorithms includes ML algorithms, which learn and make predictions and decisions without explicit programming. Traditionally coded programs also struggle with independent iteration.

Unstructured Data 75

Unstructured Data Deep Learning Cost-Benefit Machine Learning 75

CIO Business Intelligence

AUGUST 21, 2024

And, yes, enterprises are already deploying them. The flashpoint moment is that rather than being based on rules, statistics, and thresholds, now these systems are being imbued with the power of deep learning and deep reinforcement learning brought about by neural networks,” Mattmann says.

Risk 136

Risk Insurance Cost-Benefit Software 136

Domino Data Lab

JULY 2, 2019

Scale the problem to handle complex data structures. Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. Some may ask: “Can’t we all just go back to the glory days of business intelligence, OLAP, and enterprise data warehouses?”

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

IBM Big Data Hub

AUGUST 1, 2022

As a company, we have been entrusted with organizing data on a national scale, made revolutionary progress in data storing technology and have exponentially advanced trustworthy AI using aggregated structured and unstructured data from both internal and external sources. . 2000 Deep Learning: .

Unstructured Data 52

Unstructured Data Deep Learning Data Quality Data Architecture 52

IBM Big Data Hub

MAY 17, 2023

DaaS uses MAS and CP4D, which have the capability to store, organize and analyze data in the following ways: Maximo Application Suite (MAS) Maximo Application Suite is an asset management solution that manages the entire lifecycle of assets. Using object anomaly detection, the system dramatically improves production quality and speed.

Data Collection 76

Data Collection Visualization Data-driven Unstructured Data 76

CIO Business Intelligence

APRIL 27, 2022

If you trained a model on data from last month or last year, the data you feed it next month or next year is going to look wildly different.”. The applications were trained to look at terabytes of unstructured data including images, text data, video and audio to identify the right influencers for a specific brand.

Modeling 52

Modeling Advertising Unstructured Data Cost-Benefit 52

IBM Big Data Hub

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. Foundation models focused on enterprise value IBM’s watsonx.ai models are trained on IBM’s curated, enterprise-focused data lake.

Modeling 55

Modeling Cost-Benefit Machine Learning Data Lake 55

Ontotext

MAY 22, 2023

At the same time, most data management (DM) applications require 100% correct retrieval, 0% hallucination! Many enterprise data and knowledge management tasks require strict agreement, with a firm deterministic contract, about the meaning of the data. We use other deep learning techniques for such tasks.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

IBM Big Data Hub

DECEMBER 19, 2023

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements.

Machine Learning 64

Machine Learning Optimization Unstructured Data Sales 64

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

IBM Big Data Hub

JULY 6, 2023

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does. Deep learning algorithms are neural networks modeled after the human brain.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Domino Data Lab

AUGUST 10, 2021

PyTorch: used for deep learning models, like natural language processing and computer vision. It’s used for developing deep learning models. Horovod: is a distributed deep learning training framework that can be used with PyTorch, TensorFlow, Keras, and other tools. Modeling in Enterprise MLOps.

Modeling 64

Modeling IT Deep Learning Risk Management 64

IBM Big Data Hub

FEBRUARY 14, 2024

IBM Research is working to help its customers use generative models to write high-quality software code faster, discover new molecules , and train trustworthy conversational chatbots grounded on enterprise data. AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions.

Cost-Benefit 82

Cost-Benefit Insurance Machine Learning Unstructured Data 82

CIO Business Intelligence

MAY 6, 2025

Common barriers to scaling AI analytics Despite the massive investments weve seen in artificial intelligence, machine learning and enterprise analytics platforms, most organizations still struggle to move beyond the pilot phase. Data democratization is the bridge between isolated success and enterprise-wide impact.

Prescriptive Analytics 78

Prescriptive Analytics Predictive Analytics Descriptive Analytics ROI 78