The hottest Feature Engineering Substack posts right now

Everyday phenomena can be turned into numbers for mathematical analysis and optimization.
Vectorizing text, images, and sound data has led to powerful AI models.
Continuously improving vector representations of data is key for advancing AI models beyond current limitations.

Linear regression is a popular analysis method for predicting relationships between values.
Understanding the linear regression equation and scores is crucial for effective analysis.
Regression analysis can provide insights into various scenarios and help make predictions based on patterns.

Generative AI can help Data Engineers summarize vast quantities of structured and unstructured data, expanding the breadth and depth of data available.
Feature engineering using Generative AI involves ingesting unstructured data like call notes, making API calls, and transforming the data for analysis in existing pipelines.
Utilizing Generative AI for webscraping can help teams extract information efficiently from the internet, enabling monitoring of new data sources and optimizing business processes.

Natural Language Processing has evolved since 2015.
AI can assist in abstracting NLP for apartment listings, making feature extraction easier.
Utilizing ChatGPT can provide nuanced insights for apartment features, improving search efficiency.

Deep & Cross Networks (DCNs) help find multiplicative interactions in ML models
DCN-V2 uses cross layers in neural networks to improve feature learning
DCNs incorporate feature crosses effectively but may face limitations in certain data scenarios

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