Strengths2
- Clear, runnable demonstrations of audio preprocessing, dataset filtering, and transformer‑based audio inference.
- Attention visualization code provides insight into the internal workings of the AST model.
Educational Implementation · Jupyter Notebook
HF_audio
What it is
The repository contains two Jupyter notebooks that demonstrate audio processing with Librosa, dataset filtering using the PolyAI Minds-14 dataset, and inference and attention visualization of a pretrained Audio Spectrogram Transformer (AST) model.
Merit describes the code at this commit. Later pushes count once the owner rescans. How merit is scored
Where it counts
- Machine Learning80%
- Data Science40%
- Computer Vision20%
- MLOps10%
- NLP & LLMs5%
How much of the project is about each field, as scoring counts it. It ranks in the field it is most about.
What the judge found
Read from the project's code at its scored commit.
Limitations
The owner keeps this project's limitations private.
Around it on the Machine Learning board
Whole board- 103, shared rankconstelatiileserifului-ML Application · Jupyter Notebook45.6Implementationvlad andreiMachine Learning
- 103, shared rankSignal-DetectionML Application · Jupyter Notebook45.6ImplementationSuceveanu Mircea Dan SanduMachine Learning
- 105HF_audioEducational Implementation · Jupyter Notebook45.5ImplementationJamesMachine Learning
- 106Spam-ClassifierML Application · Jupyter Notebook44.8Implementationkamran akmalMachine Learning
- 107drone-position-clusteringML Application · Jupyter Notebook44.6ImplementationPop AlexandruMachine Learning
