Fix Tutorial Readme
## Python tutorials
* Main CatBoost tutorial with base features demonstration:
- * __catboost\_python\_tutorial.ipynb__
+ * [Python Tutorial](catboost_python_tutorial.ipynb)
* This tutorial shows some base cases of using catboost, such as model training, cross-validation and predicting, as well as some useful features like early stopping, snapshot support, feature importances and parameters tuning.
+* CatBoost model analysis tutorials:
+ * [Object Importance Tutorial](advanced_tutorials/catboost_object_importance_tutorial.ipynb)
+ * This tutorial shows how to evaluate importances of the train objects for test objects. And with using of importance scores detect noisy train objects.
+
+ * [SHAP Values Tutorial](advanced_tutorials/shap_values_tutorial.ipynb)
+ * This tutorial shows how to use [SHAP](https://github.com/slundberg/shap) python-package to get and visualize feature importances.
+
* CatBoost performance at different competitions:
- * __advanced\_tutorials/kaggle\_paribas.ipynb__
+ * [Kaggle Paribas Tutorial](advanced_tutorials/kaggle_paribas.ipynb)
* This tutorial shows how to get to a 9th place on paribas competition with only few lines of code and training a CatBoost model.
- * __advanced\_tutorials/mlbootcamp\_v\_tutorial.ipynb__
+ * [ML Boot Camp Tutorial](advanced_tutorials/mlbootcamp_v_tutorial.ipynb)
* This is an actual 7th place solution by Mikhail Pershin. Solution is very simple and is based on CatBoost.
* CatBoost and TensorFlow:
- * __advanced\_tutorials/quora\_catboost\_w2v.ipynb__
+ * [CatBoost & TensorFlow Tutorial](advanced_tutorials/quora_catboost_w2v.ipynb)
* This tutorial shows how to use CatBoost together with TensorFlow if you have text as input data.
* CatBoost and CoreML:
- * __advanced\_tutorials/catboost\_coreml\_export\_tutorial.ipynb__
+ * [CatBoost CoreML Tutorial](advanced_tutorials/catboost_coreml_export_tutorial.ipynb)
* This tutorial shows how to convert CatBoost model to CoreML format and use it on an iPhone.
## R tutorials
* Main CatBoost tutorial with base features demonstration:
- * __catboost\_r\_tutorial.ipynb__
+ * [R Tutorial](catboost_r_tutorial.ipynb)
* This tutorial shows how to convert your data to CatBoost Pool, how to train a model and how to make cross validation and parameter tunning.
## Command line tutorials
* Main CatBoost tutorial with base features demonstration:
- * __catboost\_cmdline\_tutorial.md__
+ * [Command Line Tutorial](catboost_cmdline_tutorial.md)
* This tutorial shows how to train and apply model with the command line tool.
## Custom loss tutorial
* Adding custom per-object error function tutorial:
- * __advanced\_tutorials/catboost\_custom\_loss\_tutorial.md__
- * This tutorial shows how to add custom per-object error function.
+ * [Custom Metrics Tutorial](advanced_tutorials/catboost_custom_metric_tutorial.md)
+ * This tutorial shows how to add custom per-object metrics.
