O'Reilly on Data

JUNE 18, 2024

Last month, TheNew York Times claimed that tech giants OpenAI and Google have waded into a copyright gray area by transcribing the vast volume of YouTube videos and using that text as additional training data for their AI models despite terms of service that prohibit such efforts and copyright law that the Times argues places them in dispute.

Advertising 354

Advertising Modeling Publishing Data Processing 354

O'Reilly on Data

DECEMBER 12, 2023

If the output of a model can’t be owned by a human, who (or what) is responsible if that output infringes existing copyright? In an article in The New Yorker , Jaron Lanier introduces the idea of data dignity, which implicitly distinguishes between training a model and generating output using a model.

Modeling 259

Modeling Software Sales Statistics 259

O'Reilly on Data

MARCH 26, 2024

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. Researchers are finding more and more ways to extract training data from ChatGPT and other models. And the space is moving quickly: SORA , OpenAI’s text-to-video model, is yet to be released and has already taken the world by storm.

Modeling 279

Modeling Machine Learning Risk Advertising 279

Analytics Vidhya

APRIL 6, 2023

Introduction This article uses to predict student performance. For many applications, including online customer service, marketing, and finance, the stock price is a crucial challenge.

Finance 300

Finance Modeling Marketing Analytics 300

O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. In this article, we turn our attention to the process itself: how do you bring a product to market? Identifying the problem.

Marketing 363

Marketing Experimentation Metrics Testing 363

IBM Big Data Hub

FEBRUARY 13, 2024

This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Generative adversarial networks (GANs) or variational autoencoders (VAEs) are used for images, videos, 3D models and music. Autoregressive models or large language models (LLMs) are used for text and language.

Enterprise 118

Enterprise Testing Modeling Data-driven 118

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

CIO Business Intelligence

JULY 24, 2024

In the long term, what we want is to have more leverage about the kinds of behaviors a model is producing.” There’s only so much you can do with a prompt if a model has been heavily trained to go against your interests,” says JJ Lopez Murphy, head of data science and AI at software development company Globant.

Risk 130

Risk Insurance Modeling Manufacturing 130

Smart Data Collective

OCTOBER 8, 2021

This article looks at how genetic algorithms (GA) and machine learning (ML) can help hedge fund organizations. Modern machine learning and back-testing; how quant hedge funds use it. Similarly, hedge funds often use modern machine learning and back-testing to analyze their quant models. Machine learning tests.

Machine Learning 109

Machine Learning Testing Strategy Modeling 109

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. Because statistics: Last is the inherently probabilistic nature of ML.

Risk 361

Risk Modeling Data Processing Software 361

Smarten

JUNE 29, 2018

This article focuses on the Independent Samples T Test technique of Hypothesis testing. What is the Independent Samples T Test Method of Hypothesis Testing? Let’s look at a sample of the Independent t-test on two variables. How Can the Independent Samples T Test Method Benefit an Organization?

Testing 40

Testing Statistics IT Business Intelligence 40

Smarten

JUNE 29, 2018

This article discusses the Paired Sample T Test method of hypothesis testing and analysis. What is the Paired Sample T Test? The Paired Sample T Test is used to determine whether the mean of a dependent variable e.g., weight, anxiety level, salary, reaction time, etc., is the same in two related groups.

Business Analysis 40

Business Analysis Testing Statistics Advertising 40

Smarten

JUNE 26, 2018

This article describes chi square test of association and hypothesis testing. What is the Chi Square Test of Association Method of Hypothesis Testing? It is used to determine whether there is a statistically significant association between the two categorical variables. Use Case – 1.

Testing 40

Testing Statistics IT Business Intelligence 40

Andrew White

MARCH 28, 2019

an analytic or metric), or some other more sophisticated representative of a model or algorithm. There was an interesting article in today’s US print edition of the Financial Times. In tests every day, if something is found to be statistically significant then it must surely be. The problem is this is not necessarily so.

Data-driven 79

Data-driven Statistics Testing Metrics 79

The Unofficial Google Data Science Blog

JANUARY 16, 2018

by SANGHO YOON In this article, we discuss an approach to the design of experiments in a network. We present data from Google Cloud Platform (GCP) as an example of how we use A/B testing when users are connected. At Google, A/B testing plays a key role in better understanding our users and products.

Testing 58

Testing Experimentation Measurement Modeling 58

CIO Business Intelligence

JUNE 11, 2024

A 1958 Harvard Business Review article coined the term information technology, focusing their definition on rapidly processing large amounts of information, using statistical and mathematical methods in decision-making, and simulating higher order thinking through applications. What comes first: A new brand or operating model?

IT 136

IT Digital Transformation Broadcasting Business Objectives 136

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 89

Data Analytics Analytics Statistics Data Collection 89

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

datapine

JANUARY 6, 2022

For a more in-depth review of scales of measurement, read our article on data analysis questions. More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. Standard deviation: this is another statistical term commonly appearing in quantitative analysis.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

Cloudera

DECEMBER 3, 2021

For example, training an interview screening model using education data often contains gender information. As discussed in this article , model design can also be a source of bias too. Even something as simple as choosing a loss function can change the bias of a trained model. Model Drift. Regulation.

Uncertainty 105

Uncertainty Measurement Metrics Risk 105

Smarten

MAY 31, 2022

When combined with Citizen Data Scientist initiatives, the adoption and use of predictive modeling and forecasting techniques can be a boon to any enterprise. Team members who have access to augmented analytics and assisted predictive modeling can plan better, predict more accurately and dependably meet goals and objectives.

Predictive Analytics 69

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 69

FineReport

MARCH 24, 2024

This article explores the data analyst job description, covering essential skills, tools, education, certifications, and experience. Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis.

Statistics 52

Statistics Data mining Visualization Reporting 52

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. The most powerful approach for the first task is to use a ‘language model’ (LM), i.e. a statistical model of natural language.

Modeling 59

Modeling Metadata Publishing Sales 59

Domino Data Lab

DECEMBER 1, 2019

This article covers how to detect data drift for models that ingest image data as their input in order to prevent their silent degradation in production. Introduction: preventing silent model degradation in production. Model monitoring: the approach. Run the example in a complementary Domino project.

Modeling 77

Modeling Machine Learning Deep Learning Testing 77

IBM Big Data Hub

DECEMBER 4, 2023

As part of our generative AI initiatives, we can demonstrate the ability to use a foundation model with prompt tuning to review the structured and unstructured data within the insurance documents (data associated with the customer query) and provide tailored recommendations concerning the product, contract or general insurance inquiry.

Insurance 53

Insurance Digital Transformation Risk Management Interactive 53

Smart Data Collective

FEBRUARY 21, 2021

A growing number of marketers are using data analytics technology to optimize their lead generation models. Combining Data Analytics with Your Lead Generation Model. Else, it is just a set of numbers that will end up as statistics. You can create it from scratch or collect a set of the most popular articles from your blog.

Strategy 98

Strategy Data Analytics Analytics Data-driven 98

Smart Data Collective

AUGUST 19, 2021

In this article, we’ll be looking at how data analytics can help in product development and where it’s going in the future. The statistics don’t lie either. Product testing and progress. From the product’s concept, it can help developers test what’s needed in order to perfect every part of the product. Image Source.

Analytics 123

Analytics Cost-Benefit Software Testing 123

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

Smart Data Collective

NOVEMBER 3, 2021

In this article, we decided to cover the tendencies in banking loan software in 2022 and give a brief market outlook of AI-driven lending software as a whole. It refers to underwriting, customer onboarding, document management, analysis, and statistics. Digital banking market. billion in net loan losses due to the pandemic burst.

Software 116

Software Data-driven Interactive Insurance 116

Ontotext

JUNE 22, 2023

Recent statistics shed light on the realities in the world of current drug development: out of about 10,000 compounds that undergo clinical research, only 1 emerges successfully as an approved drug. The current process involves costly wet lab experiments, which are often performed multiple times to achieve statistically significant results.

Metrics 52

Metrics Statistics Visualization Metadata 52

FineReport

DECEMBER 11, 2019

The article is interspersed with rich columns and pictures, introduces the basic business principles in a simple way with real cases from many companies and entrepreneurs around the world. – Head First Data Analysis: A learner’s guide to big numbers, statistics, and good decisions. By Michael Milton.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

Smart Data Collective

MARCH 23, 2020

Forbes recently wrote an article about the impact of big data on the food and hospitality industry. According to the SensorTower statistics , in 2019, a simple arcade game Stack Ball reached 100 million installs and only continued to grow. Big data is driving a number of changes in our lives. Practically, everything.

Big Data 103

Big Data Recreation/Entertainment Data mining Optimization 103

datapine

SEPTEMBER 29, 2022

In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. These needs are then quantified into data models for acquisition and delivery. 2 – Data profiling. 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Decision Management Solutions

JUNE 24, 2021

My respected colleague Neil Raden addresses this very issue in his recent article in Diginomica, “ Trustworthy AI versus ethical AI—what’s the difference, and why does it matter? ” Similarly, there are emerging tools for evaluating machine learning and AI models for bias and fairness.

Machine Learning 52

Machine Learning Testing Data-driven Modeling 52

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature. Among these, only statistical uncertainty has formal recognition.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Domino Data Lab

OCTOBER 2, 2019

This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. The case that might be familiar to you is an AB test. You can use a regression model. Introduction.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

Smarten

JUNE 20, 2018

In this article, we will focus on the identification and exploration of data patterns and the trends that data reveals. The business can use this information for forecasting and planning, and to test theories and strategies. In this article, we have reviewed and explained the types of trend and pattern analysis.

Forecasting 40

Forecasting Statistics Business Intelligence Predictive Modeling 40