O'Reilly on Data

APRIL 19, 2021

Relatively few respondents are using version control for data and models. Tools for versioning data and models are still immature, but they’re critical for making AI results reproducible and reliable. This makes sense, given that we don’t see heavy usage of tools for model and data versioning. form data).

Enterprise 358

Enterprise Risk Modeling Manufacturing 358

Smart Data Collective

AUGUST 28, 2021

Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources. On the other hand, data lakes are flexible storages used to store unstructured, semi-structured, or structured raw data.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Structured Data 140

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

Analytics Vidhya

OCTOBER 28, 2020

Overview This article will see how to create a stacked sequence to sequence the LSTM model for time series forecasting in Keras/ TF 2.0. . The post Multivariate Multi-step Time Series Forecasting using Stacked LSTM sequence to sequence Autoencoder in Tensorflow 2.0 / Keras appeared first on Analytics Vidhya.

Forecasting 245

Forecasting Modeling Analytics Deep Learning 245

CIO Business Intelligence

SEPTEMBER 12, 2024

One reason is that documents, medical records, emails, images, video, and audio and so on, are almost impossible to prepare, manage, and use in AI applications before recent technological strides in areas such as AI, computer vision, and large language models such as those used in generative AI.

Unstructured Data 111

Unstructured Data Deep Learning Metadata Structured Data 111

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Cloudera

NOVEMBER 15, 2021

In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else. The challenges of data. Data annotation. Data curation.

Unstructured Data 96

Unstructured Data Recreation/Entertainment Structured Data Reporting 96

IBM Big Data Hub

JANUARY 10, 2024

Data: AI systems learn and make decisions based on data, and they require large quantities of data to train effectively, especially in the case of machine learning (ML) models. For optimal performance, AI models should receive data from a diverse datasets (e.g.,

Unstructured Data 75

Unstructured Data Deep Learning Cost-Benefit Machine Learning 75

Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. This helps train the AI model by assigning classes to different entities in an image. The resulting structured data is then used to train a machine learning algorithm.

Machine Learning 70

Machine Learning Metrics Uncertainty Deep Learning 70

Domino Data Lab

MARCH 3, 2019

The first survey started as a simple exploration into mainstream adoption of machine learning (ML). What’s been the impact of using ML models on culture and organization? Who builds their models? We also used maturity , in other words how long had an enterprise organization been deploying ML models in production?

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 53

Data mining Machine Learning Deep Learning Marketing 53

CDW Research Hub

JULY 31, 2019

Recent advances in machine learning, and more specifically its subset, deep learning, have made it possible for computers to better understand natural language. These deep learning models can analyze large volumes of text and provide things like text summarization, language translation, context modeling, and sentiment analysis.

Deep Learning 49

Deep Learning Machine Learning Testing Modeling 49

Ontotext

FEBRUARY 26, 2024

From a technological perspective, RED combines a sophisticated knowledge graph with large language models (LLM) for improved natural language processing (NLP), data integration, search and information discovery, built on top of the metaphactory platform. Let’s have a quick look under the bonnet.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

IBM Big Data Hub

AUGUST 15, 2023

To overcome these challenges will require a shift in many of the processes and models that businesses use today: changes in IT architecture, data management and culture. A common phrase you’ll hear around AI is that artificial intelligence is only as good as the data foundation that shapes it.

IT 74

IT Data Governance Modeling Cost-Benefit 74

Smart Data Collective

MARCH 16, 2020

Deep learning is likely to play an essential role in keeping costs in check. Deep Learning is Necessary to Create a Sustainable Medicare for All System. He should elaborate more on the benefits of big data and deep learning. This underscores the need for deep learning in healthcare.

Deep Learning 84

Deep Learning Unstructured Data Cost-Benefit Big Data 84