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Zero-shot Neural Retrieval via Domain-targeted Synthetic Queries
Zero-shot learning for ad-hoc retrieval models that relies on synthetic query generation.
semantic-search question-answering information-retrieval covid-19
AIMET - Model Efficiency Toolkit
AIMET is a library that provides advanced model quantization and compression techniques for trained neural network models.
quantization model-compression aimet qualcomm
A tale of quantization in TF Lite
Model optimization strategies and quantization techniques to help deploy machine learning models in resource-constrained environments.
quantization tensorflow-lite wandb model-compression
Synthesizer: Rethinking Self-Attention in Transformer Models
The dot product self-attention is known to be central and indispensable to state-of-the-art Transformer models. But is it really required?
synthesizers transformers attention natural-language-processing
Harry Potter and the Deep Learning Experiment
RNN built with TensorFlow to generate text based on Harry Potter's books.
text-generation recurrent-neural-networks tensorflow deep-learning
Rusklainer
Identification of contribution features towards the rupture risk prediction of intracranial aneurysms using LIME explainer
interpretability machine-learning visualization lime
Interactive Machine Learning Experiments
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
machine-learning artificial-general-intelligence python javascript
Introduction to Differential Calculus
Introduces differential calculus: derivatives, partial derivatives and gradients.
differential-calculus math linear-algebra tutorial
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