IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

Experimentation 74

Experimentation Modeling Deep Learning Data-driven 74

IBM Big Data Hub

DECEMBER 5, 2023

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time. trillion in that year.

Unstructured Data 91

Unstructured Data Cost-Benefit Experimentation Machine Learning 91

Cloudera

AUGUST 20, 2020

Businesses had to literally switch operations, and enable better collaboration and access to data in an instant — while streamlining processes to accommodate a whole new way of doing things. UOB used deep learning to improve detection of procurement fraud, thereby fighting financial crime. That’s really important.

Enterprise 122

Enterprise Experimentation Uncertainty Deep Learning 122

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 72

Machine Learning Manufacturing Cost-Benefit Deep Learning 72

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Testing and Data Observability. Reflow — A system for incremental data processing in the cloud.

Testing 300

Testing Machine Learning Consulting Data Quality 300

Domino Data Lab

FEBRUARY 12, 2020

This post is for people making technology decisions, by which I mean data science team leads, architects, dev team leads, even managers who are involved in strategic decisions about the technology used in their organizations. this post on the Ray project blog ?. for reinforcement learning (RL), ? Introduction. by adding the ?@ray.remote?

Experimentation 137

Experimentation Modeling Data Science Management 137

Domino Data Lab

MAY 8, 2019

For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Machine learning model interpretability. ML model interpretability and data visualization.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105