Analytics Vidhya

AUGUST 12, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Overview This article will briefly discuss CNNs, a special variant. The post A Hands-on Guide to Build Your First Convolutional Neural Network Model appeared first on Analytics Vidhya.

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Modeling Data Science Publishing Analytics 343

Analytics Vidhya

AUGUST 26, 2021

This article was published as a part of the Data Science Blogathon “You can have data without information but you cannot have information without data” – Daniel Keys Moran Introduction If you are here then you might be already interested in Machine Learning or Deep Learning so I need not explain what it is?

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Modeling Deep Learning Machine Learning Data Science 263

CIO Business Intelligence

APRIL 22, 2022

What is data science? Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Data science gives the data collected by an organization a purpose. Data science vs. data analytics.

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Data Science Statistics Machine Learning Visualization 139

Analytics Vidhya

MAY 1, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post Topic Modelling in Natural Language Processing appeared first on Analytics Vidhya. Introduction Natural language processing is the processing of languages used.

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Modeling Data Science Publishing Analytics 180

Analytics Vidhya

JUNE 28, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In the previous article, we had started with understanding the. The post Part 2: Topic Modeling and Latent Dirichlet Allocation (LDA) using Gensim and Sklearn appeared first on Analytics Vidhya.

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Modeling Data Science Publishing Analytics 245

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.

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Data Science Statistics Business Intelligence Visualization 214

Analytics Vidhya

OCTOBER 7, 2020

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

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Modeling Data Science Publishing Analytics 296

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

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. What Are Modeling Tools? Importance of Modeling Tools. Types of Modeling Tools.

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Modeling Deep Learning Machine Learning Statistics 111

Analytics Vidhya

JUNE 27, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Let’s say you have a client who has a publishing. The post Topic Modeling and Latent Dirichlet Allocation(LDA) using Gensim and Sklearn : Part 1 appeared first on Analytics Vidhya.

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Modeling Publishing Data Science Analytics 192

FineReport

JULY 28, 2021

Good data can give you keen insights, convincing evidence to make informed decisions. By observing and analyzing data, we can develop more accurate theories and formulate more effective solutions. For this reason, data science and/vs. Definition: BI vs Data Science vs Data Analytics.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

CIO Business Intelligence

MARCH 21, 2022

What is a data scientist? Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals. Data scientist salary.

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Unstructured Data Data Analytics Analytics Structured Data 136

CIO Business Intelligence

DECEMBER 19, 2023

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. Improving search capabilities and addressing unstructured data processing challenges are key gaps for CIOs who want to deliver generative AI capabilities.

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Digital Transformation Unstructured Data Machine Learning Risk Management 142

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. Transformer models take applications such as language translation and chatbots to a new level.

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Unstructured Data Modeling Machine Learning Data mining 141

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Datasphere manages and integrates structured, semi-structured, and unstructured data types.

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Data Warehouse Metadata Digital Transformation Unstructured Data 325

CIO Business Intelligence

JANUARY 24, 2024

Generative AI and large language models (LLMs) like ChatGPT are only one aspect of AI. Model sizes: ~5 billion to >1 trillion parameters. Model sizes: ~Millions to billions of parameters. Great for: Extracting meaning from unstructured data like network traffic, video & speech.

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Deep Learning Unstructured Data Machine Learning Modeling 96

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. What Is Modeling?

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Modeling IT Risk Management Deep Learning 64

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

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Data Architecture Data Warehouse Statistics Visualization 131

DataRobot Blog

NOVEMBER 1, 2022

I love the combination of data science and sports and have been lucky to work on multiple data science projects for DataRobot, including March Mania , McLaren F1 Racing , and advised actual customers in the sports industry. This time, I am excited to apply data science to the football field. text, images).

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Unstructured Data Data Science Modeling Machine Learning 119

Analytics Vidhya

JULY 25, 2022

This article was published as a part of the Data Science Blogathon. 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. Source: [link] For […].

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Machine Learning Predictive Modeling Statistics Data Science 239

bridgei2i

OCTOBER 27, 2020

Using Data Science to Power Demand Generation in the Digital Focused Economy. The change in business models is driving more organizations to adopt digital in their business strategies. With increase in as a service business models, the customer engagement models are also evolving and this impacts the customer lifecycle.

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Data Science Sales Marketing Data-driven 75

Smart Data Collective

APRIL 5, 2022

The data science profession has become highly complex in recent years. Data science companies are taking new initiatives to streamline many of their core functions and minimize some of the more common issues that they face. IBM Watson Studio is a very popular solution for handling machine learning and data science tasks.

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Cost-Benefit Machine Learning Data Science Unstructured Data 122

Analytics Vidhya

OCTOBER 31, 2020

This article was published as a part of the Data Science Blogathon. Introduction BERT is a really powerful language representation model that has been. The post Simple Text Multi Classification Task Using Keras BERT appeared first on Analytics Vidhya.

Data Science 343

Data Science Publishing Modeling Analytics 343

Analytics Vidhya

JUNE 10, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Yes, it’s true!! Now, object detection models can be done with. The post Simplest way to do Object Detection on custom datasets appeared first on Analytics Vidhya.

Data Science 279

Data Science Publishing Modeling Analytics 279

CIO Business Intelligence

APRIL 27, 2022

This is no difference in the development of AI models, where initial results may lead teams down a new path that requires a rethinking of their AI infrastructure. “AI Models drift over time because the data that fuels them changes over time. AI is never one and done,” said Tony Paikeday, senior director of AI systems at NVIDIA.

Modeling 52

Modeling Advertising Unstructured Data Cost-Benefit 52

CIO Business Intelligence

SEPTEMBER 14, 2023

These generalists are often responsible for every step of the data process, from managing data to analyzing it. Dataquest says this is a good role for anyone looking to transition from data science to data engineering, as smaller businesses often don’t need to engineer for scale.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. The Importance of Exploratory Analytics in the Data Science Lifecycle. For one, Python remains the leading language for data science research.

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Statistics Unstructured Data Data Science Predictive Modeling 106

CIO Business Intelligence

NOVEMBER 28, 2023

With organizations seeking to become more data-driven with business decisions, IT leaders must devise data strategies gear toward creating value from data no matter where — or in what form — it resides. Unstructured data resources can be extremely valuable for gaining business insights and solving problems.

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Unstructured Data Data-driven Visualization Data Quality 128

CIO Business Intelligence

JULY 10, 2023

One of the ways Rokita is looking to stay ahead in the AI landscape is the creation of a new ChatGPT plugin that exposes Edmunds’ unstructured data—vehicle reviews, ratings, editorials—to the generative AI. The data warehouse is about past data, and models are about future data.

Data Warehouse 95

Data Warehouse Cost-Benefit Unstructured Data Machine Learning 95

Analytics Vidhya

JUNE 11, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction VGG- Network is a convolutional neural network model proposed by. The post Build VGG -Net from Scratch with Python! appeared first on Analytics Vidhya.

Data Science 172

Data Science Publishing Modeling Analytics 172

CIO Business Intelligence

DECEMBER 19, 2023

A, head of the data science practice at Hexaware. Gen AI models can sift through vast quantities of unstructured data related to bonds, identify critical information, and compare it against risk parameters. “It Hexaware conducted extensive fine-tuning to adapt the model to different industries and company types. “We

Risk 52

Risk Cost-Benefit Unstructured Data Data-driven 52

CIO Business Intelligence

AUGUST 9, 2022

These generalists are often responsible for every step of the data process, from managing data to analyzing it. Dataquest says this is a good role for anyone looking to transition from data science to data engineering, as smaller businesses often don’t need to engineer for scale. Data engineer vs. data architect.

Analytics 129

Analytics Data Science Statistics Unstructured Data 129

IBM Big Data Hub

DECEMBER 19, 2023

Anomalies are not inherently bad, but being aware of them, and having data to put them in context, is integral to understanding and protecting your business. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

Machine Learning 71

Machine Learning Optimization Unstructured Data Sales 71

CIO Business Intelligence

APRIL 25, 2022

“You can think that the general-purpose version of the Databricks Lakehouse as giving the organization 80% of what it needs to get to the productive use of its data to drive business insights and data science specific to the business. Recommendations also include suggestions for product development choices.

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Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 117

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. You can integrate different technologies or tools to build a solution.

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Unstructured Data Metadata Management Analytics 123

CIO Business Intelligence

SEPTEMBER 21, 2023

AI is now a board-level priority Last year, AI consisted of point solutions and niche applications that used ML to predict behaviors, find patterns, and spot anomalies in carefully curated data sets. Today’s foundational models are jacks-of-all-trades. This is where large language models get me really excited.

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Enterprise Consulting Modeling Cost-Benefit 130

CIO Business Intelligence

JUNE 28, 2022

Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

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Management Internet of Things Statistics Data-driven 137