O'Reilly on Data

NOVEMBER 13, 2018

Data Platforms. Over the last 12-18 months, companies that use a lot of ML and employ teams of data scientists have been describing their internal data science platforms (see, for example, Uber , Netflix , Twitter , and Facebook ). Data collection and data markets in the age of privacy and machine learning”.

Machine Learning 220

Machine Learning Risk Management Statistics 220

CIO Business Intelligence

MAY 17, 2022

Even if the AI apocalypse doesn’t come to pass, shortchanging AI ethics poses big risks to society — and to the enterprises that deploy those AI systems. The following real-world implementation issues highlight prominent risks every IT leader must account for in putting together their company’s AI deployment strategy.

Risk 142

Risk Consulting Machine Learning Data Science 142

KDnuggets

NOVEMBER 1, 2022

The unlimited access initiative provides a risk-free way to break into data science.

Data Science 115

Data Science Risk 115

IBM Big Data Hub

MAY 8, 2023

This blog continues the discussion, now investigating the risks of adopting AI and proposes measures for a safe and judicious response to adopting AI. Risk and limitations of AI The risk associated with the adoption of AI in insurance can be separated broadly into two categories—technological and usage.

Insurance 73

Insurance Risk Testing Data Quality 73

Data Science 101

APRIL 26, 2019

While it is not one of the popular programming languages for data science, The Go Programming Language (aka Golang) has surfaced for me a few times in the past few years as an option for data science. I decided to do some searching and find some conclusions about whether golang is a good choice for data science.

Data Science 111

Data Science Machine Learning Interactive Risk 111

CIO Business Intelligence

DECEMBER 19, 2023

Their steady income stream and relatively low risk compared to equities make them an especially important component of pension and retirement planning. Each type of issuer presents a different level of risk and tax treatment. A, head of the data science practice at Hexaware. Generative AI is changing the equation, though.

Risk 52

Risk Cost-Benefit Unstructured Data Data-driven 52

Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. Data Science — A Venn Diagram of Skills. Data science encapsulates both old and new, traditional and cutting-edge. 3 Components of Data Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Analytics Vidhya

MARCH 6, 2019

The post Hands-On Introduction to creditR: An Amazing R Package to Enhance Credit Risk Scoring and Validation appeared first on Analytics Vidhya. Introduction Machine learning is disrupting multiple and diverse industries right now. One of the biggest industries to be impacted – finance. Functions like fraud.

Risk 244

Risk Machine Learning Finance Analytics 244

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

Smart Data Collective

JUNE 4, 2021

What is data science? Data science is analyzing and predicting data, It is an emerging field. Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. These data models predict outcomes of new data. Where to start?

Data Science 105

Data Science Statistics Deep Learning Machine Learning 105

Dataiku

MARCH 6, 2024

As organizations scale their data science, machine learning (ML), and AI efforts, they are bound to reach this impasse, learning when to prioritize white-box models over black-box ones (because there is a time and a place for those) and how to infuse explainability along the way.

Risk 64

Risk Machine Learning Data Science Modeling 64

Smart Data Collective

MAY 23, 2021

Using data science and artificial intelligence can be useful for this type of growth. 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.

Data Science 99

Data Science Cost-Benefit Statistics Predictive Modeling 99

Analytics Vidhya

OCTOBER 17, 2022

This article was published as a part of the Data Science Blogathon. Businesses of all sizes are switching to the cloud to manage risks, improve data security, streamline processes and decrease costs, or other reasons. Introduction There are several reasons organizations should use cloud computing in the modern world.

Data Science 335

Data Science Risk Publishing Management 335

IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 77

Risk Modeling Management Metadata 77

ScienceSoft

APRIL 30, 2019

Data science with its deep learning algorithms allows for data-driven assessment of supplier risks. Is this approach good enough to undermine the position of a traditional one? Let’s explore how it works and what its advantages and limitations are.

Risk 40

Risk Data Science Deep Learning Data-driven 40

IBM Big Data Hub

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning. How MLOps will be used within the organization.

Data Science 57

Data Science Machine Learning Cost-Benefit Deep Learning 57

Analytics Vidhya

JULY 6, 2022

This article was published as a part of the Data Science Blogathon. Investing strategies vary depending on the investor’s risk appetite and goals (long term or short term). Introduction Investing Strategies are essential since they determine whether you gain or lose money.

Strategy 316

Strategy Data Science Risk Publishing 316

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. What Is Model Risk? Types of Model Risk.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

Smart Data Collective

AUGUST 27, 2019

As such, you need to exhaustively apply data science, which will help in the analysis of data from different sources to detect threats. The data scientists and the IT professionals will develop algorithms that will help in strengthening the security systems of your organization. What Is Data Science?

Data Science 83

Data Science Measurement Machine Learning Risk 83

Corinium

JUNE 24, 2020

BNP Paribas Global Head of AI and Digital Risk Analytics Adri Purkayastha talks to us about how COVID-19 is accelerating the firm’s digital transformation and the future of risk analytics. You’ve been at BNP Paribas for roughly 18 months.

Digital Transformation 370

Digital Transformation Consulting Risk Data Science 370

Smart Data Collective

MARCH 13, 2020

It doesn’t matter what the project or desired outcome is, better data science workflows produce superior results. 5 Tips for Better Data Science Workflows. Data science is a complex field that requires experience, skill, patience, and systematic decision-making in order to be successful. Adding it All Up.

Data Science 101

Data Science Key Performance Indicator Knowledge Discovery Visualization 101

Analytics Vidhya

APRIL 1, 2022

This article was published as a part of the Data Science Blogathon. Borrowers who default on loans not only damage their credit but also risk being sued […]. Introduction A loan default occurs when a borrower takes money from a bank and does not repay the loan. People often default on loans due to various reasons.

Machine Learning 297

Machine Learning Data Science Risk Publishing 297

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Smart Data Collective

AUGUST 21, 2019

They recognize that the overemphasis on big data has created problems, so they have presented alternatives. Data Science Companies Focus on Optimal Data Utilization Rather than Just Emphasizing Data Scalability. Endor is a leading pioneer in data science. This can lead to a number of problems.

Data Science 68

Data Science Big Data Data Strategy Risk 68

Alation

JULY 28, 2021

As data science processes continue to become operationalized and embedded within business processes, the importance of governing those processes continues to rise. While governance has been a major focus for many years when it comes to managing data, governance focused on data science processes is still far less mature.

Data Science 52

Data Science Data Governance Modeling Software 52

DataRobot Blog

JUNE 3, 2022

To understand the capabilities and address the risks of AI, all of us – developers, policy-makers, end-users, bystanders – must have a shared understanding of what AI is, how it can be applied to the benefit of humanity, and the risks involved when implementing it without guardrails in place to mitigate bias and harm. Download now.

Risk 52

Risk Predictive Modeling Modeling Technology 52

Domino Data Lab

FEBRUARY 20, 2019

Eugene Mandel , Head of Product at Superconductive Health , recently dropped by Domino HQ to candidly discuss cross-team collaboration within data science. Eugene Mandel , Head of Product at Superconductive Health , recently dropped by Domino HQ to discuss cross-team collaboration within data science.

Data Science 76

Data Science Testing Software Uncertainty 76

bridgei2i

NOVEMBER 25, 2020

Supply Chain Data Science in many organizations has completely transformed the market as it brings in profitability and increases sales figures. Benefits of Data Science in Supply Chain Management. Thus, the benefits of AI in data science are quite clear.

Data Science 52

Data Science Cost-Benefit Sales Predictive Analytics 52

Corinium

AUGUST 6, 2019

The Fourth Industrial Revolution is, ostensibly, upon us. The term was coined in 2016 by Klaus Schwab, the founder and executive chairman of the World Economic Form.

Risk 150

Risk Data Science 150

bridgei2i

NOVEMBER 20, 2020

Episode 2: AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. Today the Chief Risk Officers(CROs) struggle with the critical task of monitoring and assessing key risks in real time and firefight to mitigate any critical issues that arise.

Risk Management 92

Risk Management Risk Management Metrics 92

bridgei2i

APRIL 23, 2020

The banking sector globally is definitely going to see impact, some more grave than the others and most of them are announcing short to mid term measure both from a customer and business risk mitigation standpoint. Europe is in worse shape than America, with banks in UK, Italy and Germany in the risk of being in red.

Risk 52

Risk Management Scorecard Forecasting 52

Domino Data Lab

JANUARY 24, 2019

In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. Over the last couple years, it would be hard to blame anyone for being overwhelmed looking at the data science platform market landscape. Proprietary (often GUI-driven) data science platforms.

Data Science 65

Data Science Marketing Data-driven Statistics 65

Decision Management Solutions

MARCH 25, 2019

Nancy Casbarro and Deb Zawisa of Novarico recently published a new paper on Data Science in Insurance: Expansion and Key Issues subscription required) that was summarized in this nice little article on Dig-in 3 challenges facing insurers in data science implementation.

Insurance 75

Insurance Data Science Testing Modeling 75

CIO Business Intelligence

NOVEMBER 21, 2023

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT. There may be times when department-specific data needs and tools are required.

IT 131

IT Risk Cost-Benefit Risk Management 131

Analytics Vidhya

JANUARY 30, 2024

Jailbreaking and exploiting weaknesses in LLMs pose significant risks, such as misinformation generation, offensive outputs, and privacy concerns. Introduction Large Language Models (LLMs) have revolutionized the field of natural language processing, enabling machines to generate human-like text and engage in conversations.

Risk 265

Risk Modeling Analytics Deep Learning 265

Rocket-Powered Data Science

JULY 19, 2023

The latter is associated primarily with “watching” the data for interesting patterns, while precursor analytics is associated primarily with training the business systems to quickly identify those specific patterns and events that could be associated with high-risk events, thus requiring timely attention, intervention, and remediation.

Data-driven 186

Data-driven Enterprise Analytics Machine Learning 186