You can find below a list of all our major machine learning projects so far alongside an glossary of a few helpful machine learning terms. It should be noted that this glossary is extremely basic – it is only meant to provide a functional understanding of some of the terms used in our articles. For a more in-depth explanation, we encourage you to consult more detailed resources like this one.
Our Projects
The Tabla, Violin and Piano Classifier →
The Genre Classifier →
The Instrument Classifier →
The Raag Project →
The Glossary
CQT: A type of audio features which are used in machine learning.
Embeddings: The partially processed outputs of a neural network
MFCC: A type of audio features which is used in machine learning. They are supposed to mimic the experience of the human ear better than other features.
Neuron: The smallest unit of a neural network, a node which receives an input and produces an output.
TensorFlow: A machine learning Python library which we use heavily throughout our work.
Test Set: The set of data on which a model is finally tested to evaluate its performance
Training Set: The set of data on which a model is trained
Validation Set: The set of data on which the model is tested regularly to check what is needed to be done to enhance its performance.
YAMNet: A pre-existing TensorFlow model which we use to help process our data.
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Save the Sitar 
Good work. Opening new areas and relating
Thsee to music culture of this sub continent..
Cheers.
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