Скачать или смотреть How Can Pre-processing Reduce Bias In Machine Learning Data?

Machine learning models are only as good as the data they're trained on. But what if that data carries hidden biases? This video explores how intelligent pre-processing techniques can be your first line of defense against unfair and inaccurate AI outcomes.

Discover the crucial steps to building more equitable AI models:
► Understand the sources of bias in machine learning datasets, from sampling errors to historical prejudices.
► Explore key pre-processing strategies designed to detect and mitigate bias before model training.
► Learn how techniques like re-sampling, re-weighting, and attribute removal can level the playing field for your data.
► See why addressing bias early in the data pipeline is more effective than trying to correct it post-model deployment.


#AIBias, #MachineLearning, #DataScience, #EthicalAI, #TechExplained