Precisely

AUGUST 29, 2024

Key Takeaways Data quality ensures your data is accurate, complete, reliable, and up to date – powering AI conclusions that reduce costs and increase revenue and compliance. Data observability continuously monitors data pipelines and alerts you to errors and anomalies. stored: where is it located?

Data Governance 52

Data Governance Data Quality Data Observability AI 52

Data Science Dojo

NOVEMBER 15, 2023

IMPACT is a great opportunity to learn from experts in the field, network with other professionals, and stay up-to-date on the latest trends and developments in data and AI. The conference covers a wide range of topics, including deep learning, natural language processing, computer vision, and reinforcement learning.

Machine Learning 195

Machine Learning Machine Learning AI AI 195

Data Science Dojo

OCTOBER 10, 2023

Role of AI for leading professionals Here are some specific examples of how attending AI events and conferences can help individuals and organizations to learn and adapt to new technologies: A software engineer can gain knowledge about the latest advancements in natural language processing by attending an AI conference.

AI 243

AI AI Data Observability Artificial Intelligence 243

ODSC - Open Data Science

JANUARY 9, 2024

Data Engineering for Large Language Models LLMs are artificial intelligence models that are trained on massive datasets of text and code. They are used for a variety of tasks, such as natural language processing, machine translation, and summarization.

Data Engineering 97

Data Engineering Data Engineering Data Engineering Data Engineer 97

Precisely

MARCH 7, 2024

Insurance industry leaders are just beginning to understand the value that generative AI can bring to the claims management process. By harnessing the power of machine learning and natural language processing, sophisticated systems can analyze and prioritize claims with unprecedented efficiency and timeliness.

AI 72

AI AI Data Governance Data Quality 72

IBM Journey to AI blog

DECEMBER 16, 2022

And because data assets within the catalog have quality scores and social recommendations, Alex has greater trust and confidence in the data she’s using for her decision-making recommendations. This is especially helpful when handling massive amounts of big data. Protected and compliant data.

Data Quality 52

Data Quality Data Governance Data Scientist Data Wrangling 52

The MLOps Blog

JUNE 27, 2023

Learn more The Best Tools, Libraries, Frameworks and Methodologies that ML Teams Actually Use – Things We Learned from 41 ML Startups [ROUNDUP] Key use cases and/or user journeys Identify the main business problems and the data scientist’s needs that you want to solve with ML, and choose a tool that can handle them effectively.

Machine Learning 134

Machine Learning Machine Learning ML ML 134