Split notebooks into different folders

[sbalandi]

• quantization-with-accuracy-control
• rag agents

[review-notebook-app]

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[sbalandi]

@eaidova https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/quantizing-model-with-accuracy-control/speech-recognition-quantization-wav2vec2.ipynb and https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/speech-recognition-quantization/speech-recognition-quantization-wav2vec2.ipynb look similar, maybe we merge them into one or remove one ?

[eaidova]

@eaidova https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/quantizing-model-with-accuracy-control/speech-recognition-quantization-wav2vec2.ipynb and https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/speech-recognition-quantization/speech-recognition-quantization-wav2vec2.ipynb look similar, maybe we merge them into one or remove one ?

Let's stay only https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/quantizing-model-with-accuracy-control/speech-recognition-quantization-wav2vec2.ipynb (moving it to speech-recognition-quantization) as it demonstrates more advanced approach for model quantization and add mention that standard quantization (non accuracy aware) demonstrated in https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/mms-massively-multilingual-speech/mms-massively-multilingual-speech.ipynb

[sbalandi]

@eaidova https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/quantizing-model-with-accuracy-control/speech-recognition-quantization-wav2vec2.ipynb and https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/speech-recognition-quantization/speech-recognition-quantization-wav2vec2.ipynb look similar, maybe we merge them into one or remove one ?

Let's stay only https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/quantizing-model-with-accuracy-control/speech-recognition-quantization-wav2vec2.ipynb (moving it to speech-recognition-quantization) as it demonstrates more advanced approach for model quantization and add mention that standard quantization (non accuracy aware) demonstrated in https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/mms-massively-multilingual-speech/mms-massively-multilingual-speech.ipynb

moved