Reporting Bias, which was talked about in the previous paragraph that states that it is not the facts but how the facts are presented which introduces a bias. If we have a human annotator and an image captioning problem is supposed to be solved, the same image containing a man and a stra...
The most common statistic is themean. It represents the average of a dataset. Other common statistics include the median and the mode. The median is the middle value in a sorted dataset, while the mode refers to the most commonly occurring value. These measures also provide insights into the...
Algorithmic bias results in unfair outcomes due to skewed or limited input data, unfair algorithms, or exclusionary practices during AI development.
1) How is data access controlled? 2) How are passwords and credentials stored on the platform? 3) Where is the data hosted on the platform? Technical support and documentation Ensure the data annotation platform you choose provides technical support throughcomplete and updated documentationand an ...
Predictive analytics is the art of using historical & current data to make projections about what might happen in the future. Learn more for your business.
Whileunlabeled dataconsists of raw inputs with no designated outcome, labeled data is precisely the opposite. Labeled data is carefully annotated with meaningful tags, or labels, that classify the data's elements or outcomes. For example, in a dataset of emails, each email might be labeled as...
AI bias is an anomaly in the output of ML algorithms due to prejudiced assumptions. Explore types of AI bias, examples, how to reduce bias & tools to fix bias.
Text analysis is apt for transforming and making sense of unstructured data. This process helps you extract valuable information from a large dataset, easing data collection and improving decision making. Steps to Conduct Quantitative Data Analysis ...
MIT, is a synthetic data generation ecosystem of libraries “that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset,” according toSDV...
Thediscriminatoris the adversary, where thegenerativeresult (fake image) is compared against therealimages in the dataset. The discriminator tries to distinguish between the real and fake images, video or audio. GANs train themselves. The generator creates fakes while the discriminator learns to spot...