IBM Big Data Hub

MARCH 7, 2023

The worldwide statistics on premature births are staggering— the University of Oxford estimates that neonatal sepsis causes 2.5 The specific approach we took required the use of both AI and edge computing to create a predictive model that could process years of anonymized data to help doctors make informed decisions.

Risk 52

Risk Technology Informatics Predictive Modeling 52

Smarten

APRIL 25, 2024

Artificial Intelligence (AI) and Machine Learning (ML) elements support Citizen Data Scientists and help users prepare data, achieve automated data insights and create, share and use predictive models. Users can harness the power of statistics and machine learning to uncover hidden insights and improve the overall quality of your data.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

IBM Big Data Hub

JANUARY 25, 2024

We all want to see our ideal human values reflected in our technologies. We expect technologies such as artificial intelligence (AI) to not lie to us, to not discriminate, and to be safe for us and our children to use. Consider the diversity prediction theorem. .” How might this insight affect evaluation of AI models?

Predictive Modeling 87

Predictive Modeling Modeling Risk Statistics 87

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 135

Data Analytics Diagnostic Analytics Management Analytics 135

CIO Business Intelligence

APRIL 22, 2022

Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Some common tools include: SAS” This proprietary statistical tool is used for data mining, statistical analysis, business intelligence, clinical trial analysis, and time-series analysis.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

Smarten

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Descriptive Statistics. Access to Flexible, Intuitive Predictive Modeling. Trends and Patterns.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

Smarten

MAY 29, 2023

World-renowned technology analysis firm Gartner defines the role this way, ‘A citizen data scientist is a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics. ‘If Automatic generation of models.

Prescriptive Analytics 52

Prescriptive Analytics Predictive Modeling Digital Transformation Business Objectives 52

CIO Business Intelligence

JULY 24, 2023

The transformation, which started in partnership with Microsoft in 2016, is also enabling LaLiga to expand its business by offering technology platforms and services to the sports and entertainment industry at large. It has also developed predictive models to detect trends, make predictions, and simulate results.

Broadcasting 98

Broadcasting Recreation/Entertainment Testing Machine Learning 98

IBM Big Data Hub

MAY 1, 2023

Along with the explosion of information technology in the 1950’s, the term ‘artificial intelligence’ (AI) was coined by John McCarthy in 1956. The early versions of AI were capable of predictive modelling (e.g., AI is still an emerging technology and the road to implementation will have challenges.

Insurance 79

Insurance Predictive Modeling Cost-Benefit Statistics 79

O'Reilly on Data

JUNE 18, 2019

A recent O’Reilly survey found that those with mature AI practices (as measured by how long they’ve had models in production) cited “Lack of data or data quality issues” as the main bottleneck holding back further adoption of AI technologies. The models are then used to spot errors and suggest the “most probable” values to replace.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It can also be challenging to operationalize data analytics models. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 80

Data Science Data Analytics Prescriptive Analytics Analytics 80

BizAcuity

APRIL 1, 2023

Widely used to discover trends, patterns, check assumptions and spot anomalies or outliers, EDA involves a variety of techniques including statistical analysis, and machine learning to gain a better understanding of data. Building a predictive model is a continuous process and commitment.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Smarten

JUNE 17, 2022

CERT-IN , or the Indian Computer Emergency Response Team , is an India government-approved organization for upholding information technology (IT) security, and is a well-renowned application security standard, respected within the technology community.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

BizAcuity

JANUARY 18, 2023

Widely used to discover trends, patterns, check assumptions and spot anomalies or outliers, EDA involves a variety of techniques including statistical analysis, and machine learning to gain a better understanding of data. Predictive Analytics. Predictive modeling for flagging suspicious activity. These include-.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

CIO Business Intelligence

OCTOBER 13, 2023

Businesses are turning to gen AI to streamline business processes, develop proprietary AI technology, and reduce manual efforts in order to free up employees to take on more intensive tasks. Generative AI is quickly changing the landscape of the business world, with rapid adoption rates across nearly every industry.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Smart Data Collective

MAY 23, 2021

While this can be classed as data science, one difference is that data science tends to use a predictive model to make its analysis, while AI can be capable of analyzing based on learned knowledge and facts. Data science covers a broad range of techniques, including statistics, design and development. Data science.

Data Science 99

Data Science Cost-Benefit Statistics Predictive Modeling 99

Smarten

NOVEMBER 8, 2022

The Smarten advanced analytics product suite was specifically designed to support business users and those with average technology skills and offers sophisticated analytics tools in an intuitive, easy-to-use environment and this self-paced course material is a natural extension of the self-serve Smarten Augmented Analytics approach.’.

Business Intelligence 52

Business Intelligence Predictive Modeling Statistics Data-driven 52

CIO Business Intelligence

JULY 26, 2023

As for Keller Williams, Chief Technology and Digital Officer Chris Cox sees the cloud as an engine for innovation. “We Re/Max’s data chief says he approaches data management in several ways, from streaming MLS data through big data technologies stored in Snowflake, to storing data in relational database data stores. “We

Data Lake 98

Data Lake Digital Transformation Machine Learning Data Architecture 98

O'Reilly on Data

MAY 18, 2020

And last is the probabilistic nature of statistics and machine learning (ML). Most AI models decay overtime: This phenomenon, known more widely as model decay , refers to the declining quality of AI system results over time, as patterns in new data drift away from patterns learned in training data.

Risk 359

Risk Modeling Data Processing Software 359

CIO Business Intelligence

APRIL 25, 2022

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. On-site courses are available in Munich. Remote courses are also available. Switchup rating: 5.0 (out Data Science Dojo.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

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 56

Machine Learning Data Science Statistics Deep Learning 56

Data Science 101

JUNE 10, 2019

They can clean large amounts of data, explore data sets to find trends, build predictive models, and create a story around their findings. The power of data science comes from a deep understanding of statistics,algorithms, programming, and communication skills. A data scientist can run a project from end-to-end. Data Analysts.

Data Science 96

Data Science Statistics Predictive Modeling Machine Learning 96

Sisense

AUGUST 11, 2019

BA and BI are broad terms covering all kinds of technologies and approaches – and, to add to the confusion, are often used interchangeably. BA primarily predicts what will happen in the future. So…what is the difference between business intelligence and business analytics? Is there a difference at all? Let’s take a closer look.

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

CIO Business Intelligence

JULY 28, 2022

They’ve also created a relationship with universities, setting up a pipeline of emerging technology-focused interns, who work at the company, gain experience in data science, and then can potentially be hired after they graduate. . Data scientists have extensive academic backgrounds — often in computer science, statistics, and mathematics.

Data Science 143

Data Science IT Machine Learning Data-driven 143

DataRobot Blog

JULY 28, 2022

While the application of cutting-edge technology and the ability to come up with novel ideas are often the deciding factors, a simple solution based on an understanding of the essence of the problem can often be the winning solution. I thought of the solutions of the top team in a Data Science Competition for LANL Earthquake Prediction.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. When business decisions are made based on bad models, the consequences can be severe. Figure 1: The main components of a model as defined by banking industry regulators.

Risk 111

Risk Modeling IT Risk Management 111

The Data Visualisation Catalogue

APRIL 4, 2019

He’s here to explain his vision of the future with dashboards and workspaces from utilising virtual reality (VR) technology. I’ve implemented DataView in my own work and find it an excellent way to organize investment information, do data discovery and create predictive models. Especially when it came to multi-dimensional data.

Dashboards 73

Dashboards Predictive Modeling Visualization Modeling 73

Sisense

SEPTEMBER 25, 2020

A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. Statistics and programming go hand in hand. Mastering statistical techniques and knowing how to implement them via a programming language are essential building blocks for advanced analytics. Linear regression.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

FineReport

MAY 29, 2020

The ‘data’ part is the statistics and data display. . Business understanding’ is realizing in-depth data analysis and smart data forecasting via analysis and prediction functions such as data mining, predictive modeling, and so on. The key to BI software is ‘data+business understanding.’ .

Reporting 94

Reporting OLAP Visualization Software 94

Birst BI

OCTOBER 30, 2018

Fortunately, advances in analytic technology have made the ability to see reliably into the future a reality. The foundation of predictive analytics is based on probabilities. To generate accurate probabilities of future behavior, predictive analytics combine historical data from any number of applications with statistical algorithms.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

O'Reilly on Data

DECEMBER 12, 2019

The debugging techniques we propose should work on almost any kind of ML-based predictive model. But they will be easier to execute on interpretable models or with explainable ML. Luckily, technological progress has been made toward this end in recent years. There are a lot of ways to fix discrimination in ML models.

Machine Learning 192

Machine Learning Modeling Testing Risk Management 192

O'Reilly on Data

MARCH 23, 2021

On top of this, pre-existing societal biases are being reinforced and promulgated at previously unheard of scales as we increasingly integrate machine learning models into our daily lives. Put simply, we are reduced to the inputs of an algorithm. Let’s not make the mistake of assuming online community formation doesn’t have constraints.

Internet Publishing and Broadcasting 319

Internet Publishing and Broadcasting Broadcasting Data-driven Interactive 319

Insight

AUGUST 5, 2020

So I joined Maslo , whose mission is to increase self-awareness and empathy in the world using technology to capture and analyze emotional signals. Predicting mood from behavioral signals can enable artificially intelligent beings to make better empathy-led decisions and help Maslo develop state-of-the-art empathetic technology.

Predictive Modeling 98

Predictive Modeling Statistics Modeling Measurement 98

Smarten

APRIL 19, 2024

Nothing…and I DO mean NOTHING…is more prominent in technology buzz today than Artificial Intelligence (AI). In a recent survey of C-suite executives, 80% of said they believe AI will transform their organizations, and 64% said it is the most transformational technology in a generation. billion, with the market growing by 31.1%

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Domino Data Lab

NOVEMBER 17, 2020

High throughput screening technologies have been developed to measure all the molecules of interest in a sample in a single experiment (e.g., These technologies have been described as the ‘universal detection’ of molecules in cells, tissue, or organisms in an unbiased and un-targeted way [1]. Introduction. Antimicrobial. Autoimmunity.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

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. What Is Business Intelligence And Analytics?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. Manage a range of machine learning models with watstonx.ai

Machine Learning 77

Machine Learning Modeling Deep Learning Predictive Modeling 77