Smart Data Collective

SEPTEMBER 17, 2020

Nowadays, terms like ‘Data Analytics,’ ‘Data Visualization,’ and ‘Big Data’ have become quite popular. Some prominent banking institutions have gone the extra mile and introduced software to analyze every document while recording any crucial information that these documents may carry. Engaging the Workforce.

Big Data 142

Big Data Finance Risk Management Risk 142

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. Exploratory Data Analysis (EDA) EDA is used to analyze data and summarize their main properties and characteristics using visual techniques. OCR is widely used to digitize all kinds of physical documentation.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. EDA is used to analyze data and summarize their main properties and characteristics using visual techniques. OCR is widely used to digitize all kinds of physical documentation. Predictive Analytics.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

IBM Big Data Hub

AUGUST 28, 2023

Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs. Topic modeling: Topic modeling aims to discover underlying themes and/or topics in a collection of documents.

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

O'Reilly on Data

DECEMBER 12, 2019

That’s where model debugging comes in. Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Sensitivity analysis.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

CIO Business Intelligence

MARCH 5, 2024

CIOs must also partner with CISOs, legal, human resources, and business leaders to build awareness of policies and develop a generative AI risk management strategy. Today, top AI-assistant capabilities delivering results include generating code, test cases, and documentation. So, what delivers on the productivity promise today?

Cost-Benefit 112

Cost-Benefit Advertising Experimentation Software 112