Glum

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**New features:**

* The :meth:`linear_predictor` and :meth:`predict` methods of :class:`~glum.GeneralizedLinearRegressor` and :class:`~glum.GeneralizedLinearRegressorCV`
gain an ``alpha`` parameter (in complement to ``alpha_index``). Moreover, they are now able to predict for multiple penalties.

**Other:**

* Methods of :class:`~glum._link.Link` now consistently return NumPy arrays, whereas they used to preserve pandas series in special cases.
* Don't list ``sparse_dot_mkl`` as a runtime requirement from the conda recipe.
* The minimal ``numpy`` pin should be dependent on the ``numpy`` version in ``host`` and not fixed to ``1.16``.

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**Bug fix:**

- ``copy_X = False`` will now raise a value error when ``X`` has dtype ``int32`` or ``int64``. Previously, it would only raise for dtype ``int64``.

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**Tutorials and documentation improvements:**

- Adding tutorials to the documentation.
- Additional documentation improvements.

**Bug fix:**

- Verbose progress bar now working again.

**Other:**

- Small improvement in documentation for the ``alpha_index`` argument to :meth:`~glum.GeneralizedLinearRegressor.predict`.
- Pinned pre-commit hooks versions.

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We now have Windows builds!

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**Deprecations:**

- Fusing the ``alpha`` and ``alphas`` arguments for :class:`~glum.GeneralizedLinearRegressor`. ``alpha`` now also accepts array like inputs. ``alphas`` is now deprecated but can still be used for backward compatibility. The ``alphas`` argument will be removed with the next major version.

**Bug fix:**

- We removed entry points to functions in ``glum_benchmarks`` from the conda package.

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**Bug fix:**

- :func:`glum._distribution.unit_variance_derivative` is
evaluating a proper numexpr expression again (regression in 1.3.0).