Predictive Modeling and Structured Data

Predictive Modeling

Structured Data

Introduction to Linear Predictive Models – Part 2

Analytics Vidhya

JULY 30, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Welcome readers to Part 2 of the Linear predictive model series. The post Introduction to Linear Predictive Models – Part 2 appeared first on Analytics Vidhya.

Predictive Modeling

Predictive Modeling Modeling Data Science Publishing

Building Customer Churn Prediction Model With Imbalance Dataset

Analytics Vidhya

FEBRUARY 1, 2023

The amount of data is insufficient until it does not reflect or we cannot find meaningful information that can drive business […] The post Building Customer Churn Prediction Model With Imbalance Dataset appeared first on Analytics Vidhya.

Predictive Modeling

Predictive Modeling Modeling Analytics IT

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Automation, Evolved: Your New Playbook For Smarter Knowledge Work

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How to create a Stroke Prediction Model?

Analytics Vidhya

MAY 24, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon INTRODUCTION: Stroke is a medical condition that can lead to the. The post How to create a Stroke Prediction Model? appeared first on Analytics Vidhya.

Predictive Modeling

Predictive Modeling Modeling Data Science Publishing

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App Building And Deployment of a Predictive Model Using Flask and AWS

Analytics Vidhya

JUNE 20, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Objective An app is to be developed to determine whether an. The post App Building And Deployment of a Predictive Model Using Flask and AWS appeared first on Analytics Vidhya.

Predictive Modeling

Predictive Modeling Modeling Data Science Publishing

Improve your Predictive Model’s Score using a Stacking Regressor

Analytics Vidhya

DECEMBER 3, 2020

This article was published as a part of the Data Science Blogathon. Introduction The general principle of ensembling is to combine the predictions of various. The post Improve your Predictive Model’s Score using a Stacking Regressor appeared first on Analytics Vidhya.

Predictive Modeling

Predictive Modeling Data Science Publishing Modeling

Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

FEBRUARY 6, 2025

Even basic predictive modeling can be done with lightweight machine learning in Python or R. In life sciences, simple statistical software can analyze patient data. The results of these models are then combined using a simple algorithm to determine the best-performing model for a given item, which is then used for prediction.

Unstructured Data

Unstructured Data Manufacturing Data Governance Sales

Machine Learning Paradigms with Example

Analytics Vidhya

JULY 25, 2022

Machine Learning is the method of teaching computer programs to do a specific task accurately (essentially a prediction) by training a predictive model using various statistical algorithms leveraging data. Introduction Let’s have a simple overview of what Machine Learning is. Source: [link] For […].

Machine Learning

Machine Learning Predictive Modeling Statistics Data Science

IT leaders look beyond LLMs for gen AI needs

CIO Business Intelligence

MAY 21, 2024

With this model, patients get results almost 80% faster than before. Next, Northwestern and Dell will develop an enhanced multimodal LLM for CAT scans and MRIs and a predictive model for the entire electronic medical record.

IT Cost-Benefit Experimentation Forecasting

What is a customer data platform? A unified customer database

CIO Business Intelligence

MAY 10, 2022

Customer data platform defined. A customer data platform (CDP) is a prepackaged, unified customer database that pulls data from multiple sources to create customer profiles of structured data available to other marketing systems. Treasure Data CDP.

Advertising

Advertising Interactive Marketing Structured Data

Building and Evaluating GenAI Knowledge Management Systems using Ollama, Trulens and Cloudera

Cloudera

MAY 23, 2024

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes.

Management

Management Metrics Data Processing Machine Learning

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science

Data Science Data Analytics Prescriptive Analytics Analytics

Reflections on the Knowledge Graph Conference 2023

Ontotext

MAY 25, 2023

For example, knowledge graphs can be used to provide structured data to train LLM, and LLM can be used to extract information from unstructured data sources such as text and images, which can then be incorporated into knowledge graphs. Knowledge graphs will continue to be essential for AI in the era of ChatGPT and LLM.

Machine Learning

Machine Learning Structured Data Unstructured Data Predictive Modeling

How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

MARCH 7, 2023

You can use simple SQL to analyze structured and semi-structured data across data warehouses, data marts, operational databases, and data lakes to deliver the best price performance at any scale. Data in Amazon S3 can be easily queried in place using SQL with Amazon Redshift Spectrum.

Analytics

Analytics Data Warehouse Data Lake Metadata

Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

AUGUST 28, 2023

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. It weighs down frequently occurring words and emphasizes rarer, more informative terms. positive, negative or neutral).

Data mining

Data mining Machine Learning Deep Learning Marketing

What is a Data Pipeline?

Jet Global

MAY 9, 2024

Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment. API Data Pipelines : These pipelines retrieve data from various APIs and load it into a database or application for further use.

Data Lake

Data Lake Data Warehouse Business Intelligence Machine Learning

Data Leaders Brief

Introduction to Linear Predictive Models – Part 2

Building Customer Churn Prediction Model With Imbalance Dataset

Webinars

Trending Sources

How to create a Stroke Prediction Model?

Webinars

App Building And Deployment of a Predictive Model Using Flask and AWS

Improve your Predictive Model’s Score using a Stacking Regressor

Beyond the hype: Do you really need an LLM for your data?

Machine Learning Paradigms with Example

IT leaders look beyond LLMs for gen AI needs

What is a customer data platform? A unified customer database

Building and Evaluating GenAI Knowledge Management Systems using Ollama, Trulens and Cloudera

Data science vs data analytics: Unpacking the differences

Reflections on the Knowledge Graph Conference 2023

How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

Leveraging user-generated social media content with text-mining examples

What is a Data Pipeline?

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