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Engineering blog

The technology behind Feedly

Learn about machine learning and AI from the people who build Feedly

Machine learning

How Feedly vets CTI sources using Cyber Source Rank

Machine learning

Fast autoscaling on GPUs

Machine learning

How deduplication and clustering can work together to improve the reading experience

Machine learning

Feedly Ask AI: Insights from the development process

Machine learning

NLP Breakfast 13: Building intuitions before building models

Machine learning

NLP Breakfast 12: An Improved and Affordable feature-based RNN model for Language Modeling

Machine learning

NLP Breakfast 11: Structuring legal documents with Deep Learning

Machine learning

NLP Breakfast 10: Recursive Routing Networks

Machine learning

NLP Breakfast 9: BERT for Question Answering Systems

Machine learning

NLP Breakfast 8: Knowledge Distillation

Machine learning

NLP Breakfast 7: XLNet explained

Machine learning

NLP Breakfast 6: Transfer NLP

Machine learning

NLP Breakfast 5: Hierarchical Multi-Task Learning (HMTL)

Machine learning

NLP Breakfast 4: Graph Neural Networks

Machine learning

NLP Breakfast 3: Latest on Text Classification

Machine learning

NLP Breakfast 2: The Rise of Language Models

Machine learning

NLP Breakfast 1: Average Attention Network

Machine learning

Learning Context With Item2vec

Machine learning

The data science behind recommendations in Feedly

Machine learning

Tricks of the Trade: LogSumExp