Smart Data Collective

OCTOBER 8, 2023

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. This involves data collection , data cleaning, data analysis, and data interpretation.

Data Analytics 94

Data Analytics Analytics Statistics Data Collection 94

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. features) and metadata (i.e.

Modeling 59

Modeling Metadata Publishing Sales 59

CIO Business Intelligence

JUNE 5, 2023

These measures will drive decarbonization across the value chain and give CIOs the opportunity to leverage their expertise and build resiliency throughout their organizations. This opportunity to collaborate with sustainability in mind extends to the influence CIOs hold over where and how employees work.

Software 105

Software Measurement Visualization Business Objectives 105

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.

Management 332

Management Machine Learning Experimentation Metrics 332

IBM Big Data Hub

MAY 28, 2024

Virtually every organization recognizes the power of data to enhance customer and employee experiences and drive better business decisions. Yet, as data becomes more valuable, it’s also becoming harder to protect. What is a data protection strategy? Additionally, some data protection laws and regulations require them.

Strategy 45

Strategy Measurement Risk Cost-Benefit 45

CIO Business Intelligence

MARCH 30, 2022

Even when customers have tuned their rules for years with fraud analysts who know the space, we come in with machine learning models and beat them,” says Baumhof. But six years ago, when LexisNexis began to invest in machine learning as a replacement for rules-based systems, the company started with a linear regression model.

Machine Learning 144

Machine Learning Testing Risk Data-driven 144

O'Reilly on Data

OCTOBER 22, 2020

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. Since I work in the AI space, people sometimes have a preconceived notion that I’ll only talk about data and models.

Consulting 296

Consulting Risk Cost-Benefit Modeling 296

CIO Business Intelligence

MAY 16, 2023

AI Opportunities Generative AI is the basis for sophisticated AI models such as ChatGPT and Dall-E. Big Data collection at scale is increasing across industries, presenting opportunities for companies to develop AI models and leverage insights from that data. This helps to ensure accuracy and neutrality.

Advertising 100

Advertising Recreation/Entertainment Experimentation Enterprise 100

CIO Business Intelligence

FEBRUARY 13, 2023

Larger is Better involves a “lower specification limit,” such as test scores — where the target is 100%. Measure performance of the current process by establishing a data collection plan to determine defects and gather metrics. Improve the process by eliminating root causes of defects through innovative solutions.

Management 89

Management Statistics Manufacturing Measurement 89

Smart Data Collective

MARCH 28, 2022

It can be further classified as statistical and predictive modeling, but the two are closely associated with each other. Prescriptive data analytics: It is used to predict outcomes and necessary subsequent actions by combining the features of big data and AI. They can be again classified as random testing and optimization.

Data Analytics 85

Data Analytics Software Analytics Statistics 85

Decision Management Solutions

FEBRUARY 8, 2021

in partnership with IBM and other organizations is in the process of conducting performance tests on the world’s first autonomous ship and is due to set sail for its first transatlantic voyage this spring. I think you’ll see the parallels with Decision Management as the story unfolds. Marine AI—based in Plymouth, U.K.—in

Machine Learning 93

Machine Learning Testing Deep Learning Optimization 93

IBM Big Data Hub

FEBRUARY 23, 2024

DL models can improve over time through further training and exposure to more data. When a user sends a message, the system uses NLP to parse and understand the input, often by using DL models to grasp the nuances and intent. Marketing and sales: Conversational AI has become an invaluable tool for data collection.

Enterprise 100

Enterprise Interactive Data-driven Key Performance Indicator 100

IBM Big Data Hub

AUGUST 11, 2023

Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. These insights can help drive decisions in business, and advance the design and testing of applications. How the models are stored.

Data Science 56

Data Science Machine Learning Cost-Benefit Deep Learning 56

Data Science and Beyond

APRIL 5, 2021

The world has adapted quickly, though it seems like Automattic’s globally-distributed model is still quite unusual. Instead, many companies have switched to a locally-remote model, hiring remotely within the same country or timezone region. Only time will tell. Sustainability.

Experimentation 61

Experimentation Testing Publishing Measurement 61

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

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. Today, in 2022, the code (i.e.,

Experimentation 59

Experimentation Modeling Business Objectives Manufacturing 59

Domino Data Lab

OCTOBER 2, 2019

The case that might be familiar to you is an AB test. You can make a change to a product and test it against the original version of the product. The control group experiences the original algorithm, and the test group experiences the new version. You can use a regression model. Let’s continue with this example.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

Juice Analytics

MARCH 30, 2021

(3) Data Product Ecosystem To enable the flow of information and the creation and sharing of data products, you need standards, tools, and processes in place. A good example is what Apple did with the App Store in creating a platform and standards by which apps are created, tested, distributed, and reviewed.

Cost-Benefit 131

Cost-Benefit Statistics Metrics Dashboards 131

CIO Business Intelligence

SEPTEMBER 2, 2022

The average salary for a financial software engineer is $116,670 per year, with a reported salary range of $85,000 to $177,000 per year, according to data from Glassdoor. Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

The average salary for a financial software engineer is $116,670 per year, with a reported salary range of $85,000 to $177,000 per year, according to data from Glassdoor. Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications.

Finance 98

Finance IT Software Reporting 98

Jet Global

SEPTEMBER 29, 2021

Data-driven Finance leaders use metrics to look at what the business should do next, rather than only look back at how well they performed in the past. They use data and software with machine learning (artificial intelligence) to model and compare ‘what-if’ scenarios to grow the business. Provide Access to Quality Data.

Data-driven 52

Data-driven Finance Data Collection Metrics 52

Sisense

OCTOBER 29, 2020

While we are already seeing a small number of AVs being tested on our roads today, they have limited capabilities and can only drive in very specific conditions,” explained Ryan Pietzsch, a driver safety education expert with the National Safety Council, a not-for-profit organization promoting health and safety in the U.S. Advertising?

Machine Learning 90

Machine Learning Data Collection Cost-Benefit Advertising 90

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

The Unofficial Google Data Science Blog

OCTOBER 31, 2016

By PATRICK RILEY For a number of years, I led the data science team for Google Search logs. We were often asked to make sense of confusing results, measure new phenomena from logged behavior, validate analyses done by others, and interpret metrics of user behavior. Description : What’s the objective interpretation of this data?

Metrics 107

Metrics Measurement Statistics Data Collection 107

The Unofficial Google Data Science Blog

JULY 18, 2023

E ven after we account for disagreement, human ratings may not measure exactly what we want to measure. Overview Human-labeled data is ubiquitous in business and science, and platforms for obtaining data from people have become increasingly common. And for thousands of years, measurement was as simple as this.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

IBM Big Data Hub

SEPTEMBER 7, 2023

Today we are announcing our latest addition: a new family of IBM-built foundation models which will be available in watsonx.ai , our studio for generative AI, foundation models and machine learning. Collectively named “Granite,” these multi-size foundation models apply generative AI to both language and code.

Modeling 104

Modeling Risk Unstructured Data Enterprise 104

datapine

SEPTEMBER 1, 2020

Your Chance: Want to test a market research reporting software? An effective modern means of extracting real value from your research results such as brand analysis, market research reports present and arrange data in a way that is digestible and logical in equal measures through professional online reporting software and tools.

Reporting 247

Reporting Marketing KPI Dashboards 247

O'Reilly on Data

MAY 14, 2020

Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model. In reality, many candidate models (frequently hundreds or even thousands) are created during the development process. Modelling: The model is often misconstrued as the most important component of an AI product.

Management 363

Management Experimentation B2B Machine Learning 363

CIO Business Intelligence

APRIL 28, 2024

communication reliability, which supports minute-level data collection and second-level control for low-voltage transparency. It was the solution of choice to achieve an observable, measurable, adjustable, controllable and traceable low-voltage side. HPLC can deliver 99.9% Huawei also helps customers build an open ecosystem.

Interactive 85

Interactive Uncertainty Data Collection IoT 85

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Introduction. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

AUGUST 13, 2012

Yehoshua Coren: Best ways to measure user behavior in a multi-touch, multi-device digital world. Yehoshua I've covered this topic in detail in this blog post: Multi-Channel Attribution: Definitions, Models and a Reality Check. What's possible to measure. What's not possible to measure. Let's do this!

Modeling 124

Modeling Metrics Data Quality Data-driven 124

Alation

OCTOBER 12, 2022

Companies collect and analyze vast amounts of data to make informed business decisions. From product development to customer satisfaction, nearly every aspect of a business uses data and analytics to measure success and define strategies. Some examples of quantitative data include: Counts or units, stored as raw numbers.

Statistics 52

Statistics Sales Testing Marketing 52

Domino Data Lab

JUNE 23, 2019

As a result, Skomoroch advocates getting “designers and data scientists, machine learning folks together and using real data and prototyping and testing” as quickly as possible. These measurement-obsessed companies have an advantage when it comes to AI. It is similar to R&D. Transcript. Hi, I’m Peter Skomoroch.

Management 110

Management Machine Learning Experimentation Metrics 110

Cloudera

AUGUST 17, 2020

For this step, we used Spark ML in CML ( Cloudera Machine Learning ) to train a Naïve Bayes model to identify what a technical sentence looks like in the context of a case comment. Data Collection Request – A sentence requesting data from the customer. Testing the Results. Extract Technical Sentences.

Testing 82

Testing Machine Learning Interactive Metrics 82

CIO Business Intelligence

AUGUST 15, 2023

Shamim Mohammad, CIO, CarMax CarMax That volume created a Sisyphean task for the company’s content writers, as they struggled to provide up-to-date information by make, model, and year for each vehicle in the company’s constantly changing inventory. They turned to artificial intelligence to help.

IT 98

IT Manufacturing IoT Cost-Benefit 98

Cloudera

MARCH 18, 2021

The Fundamental Review of the Trading Book (FRTB), introduced by the Basel Committee on Banking Supervision (BCBS), will transform how banks measure risk. At a glance, here are the primary changes FRTB introduces: A shift from value-at-risk (VaR) to an expected shortfall (ES) measure of risk under stress. Operational Impact of FRTB.

Risk 55

Risk Machine Learning Risk Management Measurement 55

DataRobot

JULY 8, 2021

In two recent blog posts, I’ve talked about two cornerstones of trusted AI : evaluating model performance and setting up proper operational oversight. In this post, I’ll review the third and perhaps most important step: creating models that are ethical and principled. This data should not be used to train a machine learning model.

Machine Learning 52

Machine Learning Modeling Interactive Risk 52