Unite.AI

DECEMBER 27, 2024

Its not a choice between better data or better models. The future of AI demands both, but it starts with the data. Why Data Quality Matters More Than Ever According to one survey, 48% of businesses use big data , but a much lower number manage to use it successfully. Why is this the case?

Data Quality 130

Data Quality Data Drift Explainability Big Data 130

IBM Journey to AI blog

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way.

Data Scientist 234

Data Scientist Metadata Responsible AI Explainability 234

Pickl AI

JANUARY 12, 2025

For instance, in retail, AI models can be generated using customer data to offer real-time personalised experiences and drive higher customer engagement, consequently resulting in more sales. Aggregated, these methods will illustrate how data-driven, explainable AI empowers businesses to improve efficiency and unlock new growth paths.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Explainability Explainable AI 52

Pickl AI

FEBRUARY 17, 2025

Introduction: The Reality of Machine Learning Consider a healthcare organisation that implemented a Machine Learning model to predict patient outcomes based on historical data. However, once deployed in a real-world setting, its performance plummeted due to data quality issues and unforeseen biases.

Machine Learning 52

Machine Learning Algorithm Explainability Data Quality 52

The MLOps Blog

JUNE 27, 2023

Databricks Databricks is a cloud-native platform for big data processing, machine learning, and analytics built using the Data Lakehouse architecture. Delta Lake Delta Lake is an open-source storage layer that provides reliability, ACID transactions, and data versioning for big data processing frameworks such as Apache Spark.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

The MLOps Blog

AUGUST 11, 2023

Standard ML pipeline | Source: Author Advantages and disadvantages of directed acyclic graphs architecture Using DAGs provides an efficient way to execute processes and tasks in various applications, including big data analytics, machine learning, and artificial intelligence, where task dependencies and the order of execution are crucial.

ML 52

ML Machine Learning Data Ingestion Deep Learning 52

Unite.AI

JULY 5, 2024

Robust data management is another critical element. Establishing strong information governance frameworks ensures data quality, security and regulatory compliance. Accountability and Transparency: Accountability in Gen AI-driven decisions involve multiple stakeholders, including developers, healthcare providers, and end users.

Data Integration 147

Data Integration Data Quality Algorithm AI Modeling 147