O'Reilly on Data

DECEMBER 10, 2019

In that article, we talked about Andrej Karpathy’s concept of Software 2.0. We can collect many examples of what we want the program to do and what not to do (examples of correct and incorrect behavior), label them appropriately, and train a model to perform correctly on new inputs. Yes, but so far, they’re only small steps.

Software 261

Software Machine Learning Risk Data-driven 261

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. About Andrew P.

Data Governance 145

Data Governance IT Risk Data Lake 145

O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Data integration and cleaning.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

Experimentation 74

Experimentation Modeling Deep Learning Data-driven 74

Cloudera

OCTOBER 11, 2022

A recent VentureBeat article , “4 AI trends: It’s all about scale in 2022 (so far),” highlighted the importance of scalability. The article goes on to share insights from experts at Gartner, PwC, John Deere, and Cloudera that shine a light on the critical role that data plays in scaling AI. . Data science needs analytics.

Snapshot 98

Snapshot Data Science Digital Transformation Metadata 98

Rocket-Powered Data Science

JUNE 17, 2022

Synthetic monitoring is essentially digital twinning of your network and IT environment, providing insights through simulated risks, attacks, and anomalies via predictive and prescriptive modeling. Disclaimer: I was compensated as an independent freelance media influencer for my participation at the conference and for this article.

Machine Learning 238

Machine Learning Recreation/Entertainment Risk Business Objectives 238

CIO Business Intelligence

JANUARY 17, 2024

The first was becoming one of the first research companies to move its panels and surveys online, reducing costs and increasing the speed and scope of data collection. Plus, it uses LLMs like GPT-4 to generate natural language insights from data using AI techniques like natural language processing and generation.

Digital Transformation 117

Digital Transformation Dashboards Reporting Data Science 117

Smart Data Collective

OCTOBER 8, 2023

This article delves into the profound impact data analytics can have on fast food legal cases. The Power of Data Analytics: An Overview Data analytics, in its simplest form, is the process of inspecting, cleansing, transforming, and modeling data to unearth useful information, draw conclusions, and support decision-making.

Data Analytics 93

Data Analytics Analytics Statistics Data Collection 93

Analytics Vidhya

SEPTEMBER 13, 2022

This article was published as a part of the Data Science Blogathon. Introduction With technological evolution, data dependence is increasing much faster. Organizations are now employing data-driven approaches all over the world. One of the most widely used data applications […].

Predictive Analytics 284

Predictive Analytics Analytics Data-driven Data Science 284

Ontotext

DECEMBER 15, 2023

It includes only ML papers and related entities; this SPARQL query shows some statistics: papers tasks models datasets methods evaluations repos 376557 4267 24598 8322 2101 52519 153476 We can start with these repositories (most of them are on Github) and get all their topics. We use Categories as a way of finding relevant articles.

Machine Learning 69

Machine Learning Interactive Deep Learning Statistics 69

Insight

MARCH 12, 2020

The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. Instead, I built the AIgent.

Modeling 59

Modeling Metadata Publishing Sales 59

Smart Data Collective

MARCH 23, 2022

Well, if you are someone who has loads of data and aren’t using it for your surveys and you would love to learn more on how to use it, don’t go anywhere because, in this article, we will show you data mining tips you can use to leverage your surveys. 5 data mining tips for leveraging your surveys.

Data mining 120

Data mining Marketing Insurance Data Collection 120

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations.

Machine Learning 220

Machine Learning Risk Management Statistics 220

Smart Data Collective

DECEMBER 17, 2021

The process of Marketing Analytics consists of data collection, data analysis, and action plan development. Understanding your marketing data to make more informed and successful marketing strategy decisions is a systematic process. Types of Data Used in Marketing Analytics.

Marketing Analytics 93

Marketing Analytics Marketing Data-driven Analytics 93

Cloudera

AUGUST 12, 2021

The report classified employees’ reasons for leaving into six broad categories such as growth opportunity and job security, demonstrating the importance of using performance data, data collected from voluntary departures and historical data to reduce attrition for strong performers and enhance employees’ well-being.

Data-driven 111

Data-driven Manufacturing Insurance Risk Management 111

Smart Data Collective

NOVEMBER 14, 2019

They have refined their data decision-making approaches to include new predictive analytics models to forecast trends and adapt to evolving customer behavior. They have developed analytics models to address looming changes in the dynamic industry. Time series models that attempt to forecast future variable behavior.

Predictive Analytics 79

Predictive Analytics Analytics Forecasting Modeling 79

Ontotext

FEBRUARY 14, 2024

CEEL is an end-to-end transformer-based model that includes mention detection and uses entity types and entity descriptions to perform entity linking. Out of the box, the model links to Wikidata IDs. That’s why such models must use context in order to differentiate between entities, just as humans do.

Cost-Benefit 52

Cost-Benefit Modeling Metadata Optimization 52

Data Virtualization

APRIL 4, 2024

Over the past few decades, we have been storing up data and generating even more of it than we have known what. The post Querying Minds Want to Know: Can a Data Fabric and RAG Clean up LLMs? appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Integration 98

Data Integration Management Data-driven IT 98

O'Reilly on Data

OCTOBER 22, 2020

We then each chose our top three questions, which we’ve detailed in this article. Taking the time to work this out is like building a mathematical model: if you understand what a company truly does, you don’t just get a better understanding of the present, but you can also predict the future. How many people will use it?

Consulting 297

Consulting Risk Cost-Benefit Modeling 297

Rocket-Powered Data Science

JULY 7, 2019

Autonomous Vehicles: Self-driving (guided without a human), informed by data streaming from many sensors (cameras, radar, LIDAR), and makes decisions and actions based on computer vision algorithms (ML and AI models for people, things, traffic signs,…). Examples: Cars, Trucks, Taxis. See [link]. 2) Connected cars. (3) 5) Industry 4.0.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Dataiku

APRIL 22, 2022

It’s no secret that training AI models is an energy-intensive and large dataset-dependent endeavor and, to corroborate this, researchers at the University of Massachusetts Amherst performed a lifecycle assessment on large, widely accepted AI models trained on the vast datasets needed to achieve accuracy.

Experimentation 59

Experimentation Modeling Business Objectives Manufacturing 59

FineReport

MARCH 24, 2024

Given the critical role they play, employers actively seek data analysts to enhance efficiency and stimulate growth. This article explores the data analyst job description, covering essential skills, tools, education, certifications, and experience. AWS S3: Offers cloud storage for storing and retrieving large datasets.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

APRIL 14, 2022

This article was co-authored by Katherine Kennedy , an Associate at Metis Strategy. production assets with sensors to generate digitized methane detection data and indicate methane leaks, allowing them to improve safety measures onsite and lower emissions. Smarter operations through integrated data and analytics.

Strategy 109

Strategy Digital Transformation IoT Measurement 109

Smart Data Collective

NOVEMBER 24, 2020

In this article, you’ll discover: upcoming trends in business intelligence what benefits will BI provide for businesses in 2020 and on? The strategic decision-making in the future of business intelligence will be shaped by faster reports, deeper data insights, broader areas of data collection. Identify Opportunities.

Business Intelligence 130

Business Intelligence Visualization Dashboards Prescriptive Analytics 130

Smart Data Collective

MAY 28, 2021

Data security and data collection are both much more important than ever. Every organization needs to invest in the right big data tools to make sure that they collect the right data and protect it from cybercriminals. One tool that many data-driven organizations have started using is Microsoft Azure.

Data-driven 133

Data-driven Cost-Benefit Big Data Data Processing 133

IBM Big Data Hub

OCTOBER 16, 2023

Examples of AI bias in the real world show us that when discriminatory data and algorithms are baked into AI models, the models deploy biases at scale and amplify the resulting negative effects. Enable secure access to users, models and data. Safeguard AI models, data and infrastructure from adversarial attacks.

Advertising 69

Advertising Machine Learning Data Architecture Cost-Benefit 69

Smart Data Collective

MAY 17, 2021

For example, when you’re reading a physical newspaper or a magazine, it’s impossible for the media company that owns the newspaper or magazine to monitor which pages you spent the most time reading and what type of articles you prefer. We, the consumers, don’t gain much from this massive data collection and profiling.

Cost-Benefit 94

Cost-Benefit Advertising Data Collection Data-driven 94

Smart Data Collective

APRIL 23, 2022

In simple terms, big data is a term used to describe large volumes of data that are difficult to manage. This data may overwhelm businesses every day in structured or unstructured forms. Smart organizations use this data to improve their business models and make life better through analysis.

Analytics Technologies 106

Analytics Technologies Broadcasting Data Analytics Technology 106

FineReport

MARCH 7, 2024

As we explore examples of data analysis reports and interactive report data analysis dashboards, we embark on a journey to unravel the nuanced art of transforming raw data into meaningful narratives that empower decision-makers. This will be elaborated on in the third part of this article. Why Big Data Analysis Report?

Dashboards 52

Dashboards Reporting Advertising Statistics 52

datapine

JANUARY 6, 2022

Interval: a measurement scale where data is grouped into categories with orderly and equal distances between the categories. For a more in-depth review of scales of measurement, read our article on data analysis questions. Quantitative analysis refers to a set of processes by which numerical data is analyzed. Dependable.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

datapine

APRIL 21, 2022

For instance, when it comes to Human Resources, a digital transformation entails streamlining operations and digitizing personnel data. An accounting department may consider leveraging electronic contracts, data collecting, and reporting as a part of the digital transition. Approach To Digital Marketing.

Digital Transformation 206

Digital Transformation Marketing Advertising Scorecard 206

Jet Global

AUGUST 4, 2023

Learning to work with data involves developing the technical skills to manage large data sets and the soft skills to use storytelling and influencing to help audiences make data-informed decisions. In this article, we will focus on common technical skills/tools that can improve your confidence and capability to work with data.

Data Analytics 52

Data Analytics Analytics Finance Visualization 52

Smart Data Collective

MAY 4, 2023

UMass Global has a very insightful article on the growing relevance of big data in business. Big data has been discussed by business leaders since the 1990s. Professionals have found ways to use big data to transform businesses. One thing that they need to do is collect data their business needs.

Data mining 77

Data mining Big Data Data-driven Measurement 77

Smart Data Collective

MAY 1, 2022

Multiple emails, social media posts, blogs, articles, and other text forms are generated daily. Moreover, the data collected is not free from error or biases if humans handle it. Businesses are including more of it in their companies and adopting methods like AI text analysis. . What is text analysis?

Cost-Benefit 115

Cost-Benefit Unstructured Data Machine Learning Marketing 115

Smart Data Collective

SEPTEMBER 11, 2020

An article in CISCOMAG talks about the benefits of using AI in improving network security. This has the potential to transform business models and the network industry as we know it. Edge computing is a consumer-focused technology that is used to optimize data collection and processing. Edge Computing.

Technology 97

Technology IoT Internet of Things Cost-Benefit 97

Smart Data Collective

JUNE 15, 2022

According to many surveys, more than 90% of retail organizations across a wide range of sectors feel location data is crucial to their success. In fact, the popularity of location data has grown so much that it is expected to touch about $35 billion in value by 2027. 9 Ways Location Data Can Help You Excel in Retail.

Advertising 97

Advertising Cost-Benefit ROI Sales 97

Smart Data Collective

MARCH 19, 2020

In this article, we will take a close look at 3 industries using AI in 2020, while trying to dive deep into the methods and reasons behind why these areas are so ahead of the pack in terms of tech. They pointed out that the industry is never going to be the same as AI is disrupting the business model.

Big Data 96

Big Data Marketing Risk Data-driven 96