Dataiku

NOVEMBER 6, 2020

When it comes to calculating the return on investment (ROI) of data science, machine learning, and AI projects, there’s a lot to unpack. Before even jumping into the measurements and calculations, it’s important to understand the scope. Are you measuring ROI gained from a data platform or a series of data initiatives themselves? Are you modifying a previously existing strategy for tackling ROI or creating one from scratch?

ROI 68

ROI Measurement Machine Learning Data Science 68

Analytics Vidhya

NOVEMBER 6, 2020

This article was published as a part of the Data Science Blogathon. Introduction Hello! Today I am going to try my best in explaining. The post A Short Intuitive Explanation of Convolutional Recurrent Neural Networks appeared first on Analytics Vidhya.

Data Science 289

Data Science Publishing Analytics Deep Learning 289

DataCamp

NOVEMBER 6, 2020

How GPT-3 expands the world of possibilities for language tasks—and why it will pave the way for designers to prototype more easily, streamline work for data analysts, enable more robust research, and automate content generation.

IT 84

IT 84

Analytics Vidhya

NOVEMBER 6, 2020

Introduction to Artificial Intelligence and Machine Learning Artificial Intelligence (AI) and its sub-field Machine Learning (ML) have taken the world by storm. From face. The post A Comprehensive Step-by-Step Guide to Become an Industry-Ready Data Science Professional appeared first on Analytics Vidhya.

Data Science 254

Data Science Machine Learning Analytics IT 254

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

Visualization

CIO Business Intelligence

NOVEMBER 6, 2020

With Covid-19 still keeping shoppers out of stores, data-driven technology is going to be more critical than ever this year to make sure customers enjoy a seamless path to purchase. But, are retail IT organizations ready for a stay-at-home holiday season?

Data-driven 52

Data-driven Technology IT 52

Analytics Vidhya

NOVEMBER 6, 2020

This article was published as a part of the Data Science Blogathon. Introduction A model hyperparameter is a configuration that is external to the. The post Hyperparameter Tuning using Optuna appeared first on Analytics Vidhya.

Data Science 218

Data Science Publishing Modeling Analytics 218

Analytics Vidhya

NOVEMBER 6, 2020

This article was published as a part of the Data Science Blogathon. Introduction Big Data refers to a combination of structured and unstructured data. The post Big Data to Small Data – Welcome to the World of Reservoir Sampling appeared first on Analytics Vidhya.

Big Data 218

Big Data Unstructured Data Data Science Publishing 218

Andrew White

NOVEMBER 6, 2020

There was an interesting article in this week’s Economist article: Data and Governance – How the government lost its nerds. The article looks at the role of a technology platform approach to help govern, curate and share UK government data that is hidden away in silos. In a nutshell a government initiative centered on a vision, leadership and technology that led to a platform approach to a complex problem of linking data silos.

Risk 40

Risk Technology IT Analytics 40

Analytics Vidhya

NOVEMBER 6, 2020

Overview Learn about the Spark Architecture Learn about different execution modes Introduction Apache Spark is a unified computing engine and a set of. The post Data Engineering for Beginners – Get Acquainted with the Spark Architecture appeared first on Analytics Vidhya.

Analytics 206

Analytics Management 206

erwin

NOVEMBER 6, 2020

Prashant Parikh, erwin’s Senior Vice President of Software Engineering, talks about erwin’s vision to automate every aspect of the data governance journey to increase speed to insights. The clear benefit is that data stewards spend less time building and populating the data governance framework and more time realizing value and ROI from it. . Industry analysts and other people who write about data governance and automation define it narrowly, with an emphasis on artificial intelligence (AI) and

Data Governance 97

Data Governance Metadata Data-driven Visualization 97

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

Management