<commit_before>stanford-mir
============

Instructional material for the [Music Information Retrieval Workshop](https://ccrma.stanford.edu/workshops/music-information-retrieval-2017) at CCRMA, Stanford University, 2014-17.

The 2017 workshop is sold out and beyond capacity. Sorry.


How to Use This Repo
--------------------

This repository contains Jupyter notebooks related to music information retrieval (MIR). Inside these notebooks are Python code snippets that illustrate basic MIR systems.

The simplest way to use this repository is to (1) browse a read-only version of this repo at [musicinformationretrieval.com](http://musicinformationretrieval.com), and (2) follow along using a blank Jupyter notebook of your own.

### Install Python and relevant libraries

1.  If you’re totally new, the simplest solution is to download and install [Anaconda for Python 2 (2.7)](https://www.continuum.io/downloads), not Python 3. 
    
2.  Install [librosa](https://librosa.github.io/librosa/install.html) and [ffmpeg](https://librosa.github.io/librosa/install.html#ffmpeg).


### Start the Jupyter Notebook

A majority of our instruction and laboratory work will occur inside the [Jupyter notebook](http://jupyter.org/). You can think of the Jupyter notebook like the Mathematica or Matlab desktop, except it uses Python and it runs inside your web browser.

1.  Start the Jupyter notebook server on your local machine. For Mac users, at the Terminal:

        your-local-machine:~$ jupyter notebook

    For Windows users, open the application "Jupyter Notebook". Alternatively for Windows: open the application "Anaconda Prompt" and type in `jupyter notebook`.

2.  On your local machine, visit <http://localhost:8888> inside a web browser. 

3.  To open a new notebook, click on *New* near the top right. This is your scrap notebook. <commit_msg>don't forget to upgrade<commit_after>stanford-mir
============

Instructional material for the [Music Information Retrieval Workshop](https://ccrma.stanford.edu/workshops/music-information-retrieval-2017) at CCRMA, Stanford University, 2014-17.

The 2017 workshop is sold out and beyond capacity. Sorry.


How to Use This Repo
--------------------

This repository contains Jupyter notebooks related to music information retrieval (MIR). Inside these notebooks are Python code snippets that illustrate basic MIR systems.

The simplest way to use this repository is to (1) browse a read-only version of this repo at [musicinformationretrieval.com](http://musicinformationretrieval.com), and (2) follow along using a blank Jupyter notebook of your own.

### Install Python and relevant libraries

1.  If you’re totally new, the simplest solution is to download and install [Anaconda for Python 2 (2.7)](https://www.continuum.io/downloads), not Python 3. 
    
2.  Install [librosa](https://librosa.github.io/librosa/install.html) and [ffmpeg](https://librosa.github.io/librosa/install.html#ffmpeg).

If these packages are already installed, don't forget to upgrade them before the workshop. Use either `pip install --upgrade` or `conda upgrade` depending upon which package installer you used for the respective package.

### Start the Jupyter Notebook

A majority of our instruction and laboratory work will occur inside the [Jupyter notebook](http://jupyter.org/). You can think of the Jupyter notebook like the Mathematica or Matlab desktop, except it uses Python and it runs inside your web browser.

1.  Start the Jupyter notebook server on your local machine. For Mac users, at the Terminal:

        your-local-machine:~$ jupyter notebook

    For Windows users, open the application "Jupyter Notebook". Alternatively for Windows: open the application "Anaconda Prompt" and type in `jupyter notebook`.

2.  On your local machine, visit <http://localhost:8888> inside a web browser. 

3.  To open a new notebook, click on *New* near the top right. This is your scrap notebook. 
{'fraction_non_alphanumeric': 0.09081658611040448, 'fraction_numerical': 0.01475451539048588, 'mean_word_length': 4.249666221628838, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 8, 'lorem ipsum': 0, 'www.': 2, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 4, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '996182', 'n_tokens_mistral': 1135, 'n_tokens_neox': 1064, 'n_words': 486}