Marktechpost

MAY 8, 2024

In this framework, an agent, like a self-driving car, navigates an environment based on observed sensory data, taking actions to maximize cumulative future rewards. DRL models, such as Deep Q-Networks (DQN), estimate optimal action policies by training neural networks to approximate the maximum expected future rewards.

Deep Learning 122

Deep Learning Neural Network Data Scarcity Natural Language Processing 122

Marktechpost

OCTOBER 11, 2024

The core of Distilabel’s framework revolves around the GAN architecture, which includes two primary neural networks: a generator and a discriminator. The competitive dynamic between the two networks allows for continuous refinement of the synthetic data.

Data Scarcity 109

Data Scarcity Neural Network Natural Language Processing Machine Learning 109

Viso.ai

DECEMBER 18, 2023

Instead of relying on organic events, we generate this data through computer simulations or generative models. Synthetic data can augment existing datasets, create new datasets, or simulate unique scenarios. Specifically, it solves two key problems: data scarcity and privacy concerns. Technique No.1:

Computer Vision 52

Computer Vision Neural Network Auto-complete Data Scarcity 52