datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

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. Licensed by MIT, SpaCy was made with high-level data science in mind and allows deep data mining.

Unstructured Data 142

Unstructured Data Modeling Machine Learning Data mining 142

Analytics Vidhya

OCTOBER 8, 2020

This article was published as a part of the Data Science Blogathon. Introduction Fastai is a popular open-source library used for learning and practicing. The post Develop and Deploy an Image Classifier App Using Fastai appeared first on Analytics Vidhya.

Data Science 386

Data Science Publishing Analytics Unstructured Data 386

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs.

Data mining 58

Data mining Machine Learning Deep Learning Marketing 58

Analytics Vidhya

OCTOBER 7, 2020

This article was published as a part of the Data Science Blogathon. Introduction The article covers the use of Generative Adversarial Networks (GAN), an. The post Boost Model Accuracy of Imbalanced COVID-19 Mortality Prediction Using GAN-based Oversampling Technique appeared first on Analytics Vidhya.

Modeling 296

Modeling Data Science Publishing Analytics 296

bridgei2i

OCTOBER 7, 2020

But the sheer volume of data might cloud manual judgments and here is where automation and digitization could help. Insurers are leveraging the benefits of advanced data science skills at several stages of Sales & Underwriting in a digital environment. Increased Role of automation and AI in Sales & Underwriting.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

Domino Data Lab

AUGUST 9, 2021

With the right tools, your data science teams can focus on what they do best – testing, developing and deploying new models while driving forward-thinking innovation. In general terms, a model is a series of algorithms that can solve problems when given appropriate data. It’s most helpful in analyzing structured data.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Testing 307

Testing Machine Learning Consulting Data Quality 307

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code.

Modeling 64

Modeling IT Risk Management Deep Learning 64

IBM Big Data Hub

JANUARY 10, 2024

Artificial intelligence (AI) refers to the convergent fields of computer and data science focused on building machines with human intelligence to perform tasks that would previously have required a human being. For example, learning, reasoning, problem-solving, perception, language understanding and more.

Unstructured Data 83

Unstructured Data Deep Learning Cost-Benefit Modeling 83

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

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Doesn’t this seem like a worthy goal for machine learning—to make the machines learn to work more effectively?

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

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. That’s where the foundation model enters the picture. They can also quickly and accurately translate marketing collateral into multiple languages.

Modeling 60

Modeling Cost-Benefit Data Lake Machine Learning 60

CIO Business Intelligence

JANUARY 20, 2023

Modern compute infrastructures are designed to enhance business agility and time to market by supporting workloads for databases and analytics, AI and machine learning (ML), high performance computing (HPC) and more. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

Analytics 137

Analytics Key Performance Indicator Unstructured Data IoT 137