IBM Big Data Hub

OCTOBER 3, 2023

Every week during football season, an estimated 60 million Americans pore over player statistics, point projections and trade proposals, looking for those elusive insights to guide their roster decisions and lead them to victory. But numbers only tell half the story. These features help us do just that.”

Modeling 92

Modeling Statistics Consulting Unstructured Data 92

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.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

CIO Business Intelligence

JANUARY 15, 2024

If software vendors have their way, the answer is likely to involve more artificial intelligence. Sales statistics Two recent surveys concur that only a tiny minority of retailers have no plans to implement AI today. SAP will also progressively extend its existing Predictive Replenishment tool to store level.

Sales 81

Sales Software Forecasting Statistics 81

Rocket-Powered Data Science

JULY 6, 2023

These AI applications are essentially deep machine learning models that are trained on hundreds of gigabytes of text and that can provide detailed, grammatically correct, and “mostly accurate” text responses to user inputs (questions, requests, or queries, which are called prompts). Guess what? It isn’t.

Statistics 152

Statistics Deep Learning Machine Learning Modeling 152

O'Reilly on Data

DECEMBER 12, 2023

If a human writes software to generate prompts that in turn generate an image, is that copyrightable? If the output of a model can’t be owned by a human, who (or what) is responsible if that output infringes existing copyright? The word “teaching” arguably invests too much humanity into what is still software and silicon.)

Modeling 248

Modeling Software Sales Statistics 248

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. Data analytics greatly improves decision-making capabilities since they use valid data and statistics to arrive at a decision rather than going by blind faith.

Data Analytics 85

Data Analytics Software Analytics Statistics 85

IBM Big Data Hub

OCTOBER 29, 2019

So, is it any wonder that software has followed suit? In this blog, we’ll look at the differences between an SPSS Statistics Subscription and the traditional on-premises license that was the only way to purchase SPSS Statistics up until 2017. Now, you can choose which licensing model is best for your business.

Statistics 65

Statistics Software Modeling IT 65

Data Science and Beyond

JANUARY 11, 2020

Being a data scientist can sometimes feel like a race against software innovations. Every interesting and useful problem is bound to become a software commodity. Sentiment analysis is a commodity – using it in practice is a software engineering problem. Moving forward in my PhD, I got into topic modelling.

Software 103

Software Data Science Machine Learning Deep Learning 103

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. This is like a denial-of-service (DOS) attack on your model itself.

Modeling 219

Modeling Machine Learning Predictive Modeling Consulting 219

O'Reilly on Data

DECEMBER 12, 2019

Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

Machine Learning 187

Machine Learning Modeling Testing Risk Management 187

O'Reilly on Data

NOVEMBER 28, 2023

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. 16% of respondents working with AI are using open source models. A few have even tried out Bard or Claude, or run LLaMA 1 on their laptop.

Enterprise 267

Enterprise Modeling Testing Reporting 267

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. According to Gartner, the goal is to design, model, align, execute, monitor, and tune decision models and processes. Model-driven DSS. They emphasize access to and manipulation of a model.

Data mining 123

Data mining Data-driven Statistics OLAP 123

Alation

JUNE 2, 2022

These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. Currently, models are managed by modelers and by the software tools they use, which results in a patchwork of control, but not on an enterprise level. And until recently, such governance processes have been fragmented.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

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. And last is the probabilistic nature of statistics and machine learning (ML).

Risk 357

Risk Modeling Data Processing Software 357

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. The process of creating models is called modeling.

Modeling 64

Modeling IT Risk Management Deep Learning 64

CIO Business Intelligence

OCTOBER 26, 2023

Through use of data analytics, data visualization, and data modeling techniques and technologies, BI analysts can identify trends that can help other departments, managers, and executives make business decisions to modernize and improve processes in the organization.

Business Intelligence 124

Business Intelligence Data-driven Statistics Data Warehouse 124

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 120

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 120

Jet Global

APRIL 5, 2021

Enterprises actively use financial modeling to guide their financial planning and strategic decision-making. Financial models offer data-driven, quantitative analysis that tells you where your company stands and where it’s heading. That being said, one model can’t do it all. What Is Financial Modeling?

Modeling 98

Modeling Forecasting Metrics Finance 98

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. It helps to automate and makes the usage of the R programming statistical language easier and much more effective. perfect for statistical computing and design.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Smart Data Collective

OCTOBER 14, 2019

For current and future software development companies that want to be knowledgeable about using data and analysis, a few big data skillsets will help give them leverage in the coming year. Businesses need software developers that can help ensure data is collected and efficiently stored. Quantitative Analysis. Programming Language.

Big Data 74

Big Data Software Data mining Prescriptive Analytics 74

The Unofficial Google Data Science Blog

SEPTEMBER 30, 2016

The statistics app for Google Sheets hopes to change that. Editor's note: We've mostly portrayed data science as statistical methods and analysis approaches based on big data. Introduction Statistics for Google Sheets is an add-on for Google Sheets that brings elementary statistical analysis tools to spreadsheet users.

Statistics 53

Statistics Big Data Data Science Marketing 53

datapine

MARCH 31, 2022

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

CIO Business Intelligence

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance.

Data Analytics 123

Data Analytics Diagnostic Analytics Management Analytics 123

datapine

JANUARY 24, 2021

Try our professional data analysis software for 14 days, completely free! By asking the right questions, utilizing sales analytics software that will enable you to mine, manipulate and manage voluminous sets of data, generating insights will become much easier. Try our professional data analysis software for 14 days, completely free!

IT 317

IT Statistics KPI Data-driven 317

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. Try our professional BI and analytics software for 14 days free!

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. On the machine learning side, we are entering what Andrei Karpathy, director of AI at Tesla, dubs the Software 2.0

Machine Learning 343

Machine Learning Statistics Data Quality Modeling 343

FineReport

APRIL 26, 2020

Data visualization software is an application that helps you to transforms raw data in easy to understand graphical formats. Various data visualization software on the market specializes in different data visualization types. To help you faster find the data visualization software, I categorized these tools into different types.

Visualization 98

Visualization Software Dashboards Reporting 98

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. Drag-and-drop Modeler for creating pipelines, IBM integrations.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

CIO Business Intelligence

NOVEMBER 20, 2023

In retail, for example, software has been the fastest-growing job category ; about half of the world’s software engineers work outside the tech industry. The US Bureau of Labor Statistics has projected that the number of software developers will grow 25% from 2021-31. million in the United States. That isn’t easy.

Measurement 113

Measurement Metrics Software Testing 113

CIO Business Intelligence

OCTOBER 13, 2023

Application data architect: The application data architect designs and implements data models for specific software applications. Data scientists are experts in applying computer science, mathematics, and statistics to building models.

Data Architecture 122

Data Architecture Data Warehouse Statistics Visualization 122

O'Reilly on Data

OCTOBER 18, 2022

What if a named entity recognition (NER) system, based on a cutting-edge large language model (LLM), fails for Chinese, Cyrillic, or Arabic text? Audit has been an integral aspect of model risk management (MRM) in consumer finance for years, and colleagues at BLDS and QuantUniversity have been conducting model audits for some time.

Risk Management 287

Risk Management Risk Testing Measurement 287

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 255

Machine Learning Data Quality Statistics Modeling 255

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Models can be designed, for instance, to discover relationships between various behavior factors.

Predictive Analytics 134

Predictive Analytics Analytics Predictive Modeling Forecasting 134

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. Before I continue, it’s important to emphasize that machine learning is much more than building models. Model lifecycle management.

Machine Learning 217

Machine Learning Risk Management Statistics 217

O'Reilly on Data

AUGUST 4, 2022

DeepMind’s Gato is an AI model that can be taught to carry out many different kinds of tasks based on a single transformer neural network. The achievement of note is that it’s underpinned by a single model trained across all tasks rather than different models for different tasks and modalities. billion parameters.

Machine Learning 257

Machine Learning Modeling Statistics Software 257

IBM Big Data Hub

JUNE 26, 2023

According to the recent statistics released by a local auto industry association, the sales of China’s fuel vehicle market have declined for three consecutive years. The model has learned the rules behind the internal orders corresponding to general orders. However, the first roadblock is its outdated way of data transmission.

Software 62

Software Manufacturing Optimization Digital Transformation 62

The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate. And sometimes even if it is not[1].)

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52