Google's open-source deep learning framework. Was the dominant framework for years before PyTorch overtook it in research. Still widely used in production, especially for mobile (TensorFlow Lite) and web (TensorFlow.js) deployment. TensorFlow 2.0 adopted Keras as its high-level API for easier use.
The most popular deep learning framework, developed by Meta.
A subset of machine learning that uses neural networks with many layers (hence 'deep') to learn complex patterns from large amounts of data.
A mathematical function applied to a neuron's output that introduces non-linearity into the network.
An optimization algorithm that combines the best parts of two other methods — AdaGrad and RMSProp.
Artificial General Intelligence.
The research field focused on making sure AI systems do what humans actually want them to do.
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