22 Mar

The Persistent Problem Of Cultural Discrimination In AI Datasets

Researchers at Carnegie Mellon University recently conducted an NLP study on social biases present in Bollywood and Hollywood using their AI tool. Subtitles from 700 films were gathered for each industry and analysed, representing seven decades of cultural evolution. The AI tool was trained to complete sentences after learning from the subtitles and progressed to…

The post The Persistent Problem Of Cultural Discrimination In AI Datasets appeared first on Analytics India Magazine.

22 Mar

The Persistent Problem Of Cultural Discrimination In AI Datasets

Researchers at Carnegie Mellon University recently conducted an NLP study on social biases present in Bollywood and Hollywood using their AI tool. Subtitles from 700 films were gathered for each industry and analysed, representing seven decades of cultural evolution. The AI tool was trained to complete sentences after learning from the subtitles and progressed to…

The post The Persistent Problem Of Cultural Discrimination In AI Datasets appeared first on Analytics India Magazine.

21 Mar

Making Your Data Analysis Compelling

Imagine you have spent hours on data analysis at your boss’s behest. You put in a lot of effort to make your final product accurate, insightful and well packaged. But in the end, your boss decides to not use your presentation, and all your efforts go down the drain. There is nothing more frustrating than…

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21 Mar

Complete Guide to PyKeen: Python KnowlEdge EmbeddiNgs for Knowledge Graphs

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image-21044

Pykeen is a python package that generates knowledge graph embeddings while abstracting away the training loop and evaluation. The knowledge graph embeddings obtained using pykeen are reproducible, and they convey precise semantics in the knowledge graph.

The post Complete Guide to PyKeen: Python KnowlEdge EmbeddiNgs for Knowledge Graphs appeared first on Analytics India Magazine.

21 Mar

How To Detect Objects With Detection Transformers?

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image-21042

DETR(Detection Transformer) is an end to end object detection model that does object classification and localization i.e boundary box detection. It is a simple encoder-decoderTransformer with a novel loss function that allows us to formulate the complex object detection problem as a set prediction problem.

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