Analytics Vidhya

MAY 24, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon I started learning machine learning recently and I think cross-validation is. The post “I GOT YOUR BACK” – Cross validation to Models. appeared first on Analytics Vidhya.

Modeling 287

Modeling Machine Learning Data Science Publishing 287

Analytics Vidhya

JUNE 16, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Using the machine learning models in your projects is quite. The post Getting Started with Machine Learning?—?Implementing

Machine Learning 143

Machine Learning Data Science Publishing Modeling 143

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 321

Predictive Modeling Modeling Data Science Publishing 321

Analytics Vidhya

APRIL 28, 2021

ArticleVideo Book Hierarchical Modelling Hierarchical modeling also referred to as a nested model, deals with data with the observations in a certain group. The post Mixed-effect Regression for Hierarchical Modeling (Part 1) appeared first on Analytics Vidhya.

Modeling 309

Modeling Analytics Structured Data Machine Learning 309

Analytics Vidhya

MAY 19, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Everything is going to be connected to cloud and data… The post Build Interactive Models With R Shiny! appeared first on Analytics Vidhya.

Interactive 281

Interactive Modeling Data Science Publishing 281

Analytics Vidhya

AUGUST 3, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Regularization came out to be an essential technique for reducing. The post Performance Comparision of Regularized and Unregularized Regression Models appeared first on Analytics Vidhya.

Modeling 323

Modeling Data Science Publishing Analytics 323

DataRobot Blog

JANUARY 17, 2023

Recently, a prospective customer asked me how I reconcile the fact that DataRobot has multiple very successful investment banks using DataRobot to enhance the P&L of their trading businesses with my comments that machine learning models aren’t always great at predicting financial asset prices. For price discovery (e.g.,

Machine Learning 87

Machine Learning Marketing Experimentation Modeling 87

Analytics Vidhya

JUNE 23, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Hyperparameters for a model can be chosen using several techniques such. The post Performance Comparision of Tuned and Untuned Classification Models appeared first on Analytics Vidhya.

Modeling 253

Modeling Data Science Publishing Analytics 253

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 256

Predictive Modeling Modeling Data Science Publishing 256

Analytics Vidhya

JULY 27, 2022

Introduction The other day, I was reading “Natural Language Processing with Transformers” a book authored by Lewis Tunstall, Leandro von Werra, and Thomas Wolf. In it, I came across Scaling laws and challenges associated with scaling Transformer models. This topic also included excerpts […].

Data Science 371

Data Science Publishing Modeling Analytics 371

Analytics Vidhya

JULY 31, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Model overfitting is a serious problem and can cause the. The post Prevent Overfitting Using Regularization Techniques appeared first on Analytics Vidhya.

Data Science 329

Data Science Publishing Modeling Analytics 329

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 132

Data mining Data-driven Statistics OLAP 132

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. To better understand this, imagine a chatbot that helps travelers book their travel.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

Analytics Vidhya

MAY 17, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Cancer is a significant burden on our healthcare system which. The post Predictive Analytics for Personalized Cancer Diagnosis appeared first on Analytics Vidhya.

Predictive Analytics 154

Predictive Analytics Analytics Data Science Publishing 154

CDW Research Hub

JULY 31, 2019

For instance, a level 1 travel bot can provide a link for you to book travel. Recent advances in machine learning, and more specifically its subset, deep learning, have made it possible for computers to better understand natural language. NLU is able to do two things?—?intent intent classification and entity extraction.

Deep Learning 49

Deep Learning Machine Learning Testing Modeling 49

Ontotext

SEPTEMBER 7, 2023

Doug : The reason I bring up ChatGPT and Large Language Models (LLM) is because they are helping graphs to get into mainstream adoption and for people to understand them. This gets back to ChatGPT and LLMs, where you’re trying to find patterns in data that wouldn’t necessarily be there in a traditional database model.

Technology 59

Technology Visualization Digital Transformation Management 59

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Text, images, audio, and videos are common examples of unstructured data.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

CDW Research Hub

AUGUST 14, 2019

In this post, we’ll look at structuring happy and unhappy conversation paths, various machine learning policies and configurations to improve your dialogue model, and use a transfer learning-based language model to generate natural conversations. Now let’s tell our model to invoke the booking form action.

Interactive 53

Interactive Modeling Machine Learning Testing 53

Sisense

JUNE 30, 2020

When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations. Visua l analytics does the “heavy lifting” with data, by using a variety of processes — mechanical, algorithms, machine learning , natural language processing, etc — to identify and reveal patterns and trends.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Jet Global

MAY 9, 2024

For example, migrating customer data from an on-premises database to a cloud-based CRM system. Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52