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📝 Fix links in Readme
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Readme.rst

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@@ -53,7 +53,7 @@ More about uplift modelling problem read in russian on habr.com: `Part 1`_ and `
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* Applying any estimator adheres to scikit-learn conventions;
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* All approaches can be used in sklearn.pipeline (see example (`EN <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_EN.ipynb>`_ |Open In Colab3|_, `RU <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_RU.ipynb>`_ |Open In Colab4|_))
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* All approaches can be used in sklearn.pipeline (see example (`EN <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_EN.ipynb>`__ |Open In Colab3|_, `RU <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_RU.ipynb>`__ |Open In Colab4|_))
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* Almost all implemented approaches solve both the problem of classification and regression;
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Quick Start
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-----------
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See the **RetailHero tutorial notebook** (`EN <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero_EN.ipynb>`_ |Open In Colab1|_, `RU <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero.ipynb>`_ |Open In Colab2|_) for details.
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See the **RetailHero tutorial notebook** (`EN <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero_EN.ipynb>`__ |Open In Colab1|_, `RU <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero.ipynb>`__ |Open In Colab2|_) for details.
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**Train and predict uplift model**
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docs/tutorials.rst

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It is better to start scikit-uplift from the basic tutorials.
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* `The overview of the basic approaches to solving the Uplift Modeling problem`_
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* In English: `nbviewer <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero_EN.ipynb>`_ | `github <https://github.com/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero_EN.ipynb>`_ |Open In Colab1|
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* In Russian: `nbviewer <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero.ipynb>`_ | `github <https://github.com/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero.ipynb>`_ |Open In Colab2|
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* In English: `nbviewer <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero_EN.ipynb>`__ | `github <https://github.com/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero_EN.ipynb>`__ |Open In Colab1|
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* In Russian: `nbviewer <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero.ipynb>`__ | `github <https://github.com/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero.ipynb>`__ |Open In Colab2|
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* `Example of usage model from sklift.models in sklearn.pipeline`_
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* In English: `nbviewer <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_EN.ipynb>`_ | `github <https://github.com/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_EN.ipynb>`_ |Open In Colab3|
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* In Russian: `nbviewer <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_RU.ipynb>`_ | `github <https://github.com/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_RU.ipynb>`_ |Open In Colab4|
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* In English: `nbviewer <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_EN.ipynb>`__ | `github <https://github.com/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_EN.ipynb>`__ |Open In Colab3|
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* In Russian: `nbviewer <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_RU.ipynb>`__ | `github <https://github.com/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_RU.ipynb>`__ |Open In Colab4|

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