MAINT: point out HMMLearn

New repository for the HMM code
Merge pull request #2955 from larsmans/less-blas

[MRG+1] use CBLAS instead of Fortran BLAS in Liblinear
TST remove n_jobs=-1 usages in tests
ENH pairwise L1 distances for sparse matrices

Simple, O(n_features) temp space algorithm: densify row by row, then
subtract and compute L1 norm.

Added BLAS support code (cblas_dasum) to speed this up by a factor of
two on x86-64 w/ GCC and ATLAS for pair of 93% sparse matrices of shape
1000*3000. That's an order of magnitude faster than the dense version.

Also cleaned up chi2 kernel code while I was at it and added a nogil decl.
DOC example rendering
FIX TfidfVectorizer to no longer ignore binary param

Also changed the docs to clarify that binary=True means
binary tf, not binary output.
DOC: add OkCupid testimonial
Merge pull request #2997 from GaelVaroquaux/okcupid_testimonial

DOC: add OkCupid testimonial
Merge pull request #2982 from kmike/fix-macos-hangs

[MRG+1] MacOS X testing improvements
adding test for csc and csr sparse matrix
DOC use hyperlink colour when in tt
Merge pull request #3003 from jnothman/hyperlinked_tt_colour

DOC use hyperlink colour when in tt
adding change to whats_new
FIX: more robust skip of implicit constructor

Parameter introspection requires introspecting the keyword arguments of the
constructor of Python classes deriving from BaseEstimator.

This can be problematic for classes that do not override the default
constructor. Introspecting the implicit constructor used to raise a TypeError
but this is no longer the case in Python 3.4+. Hence with use a explicit check
for the implicit constructor prior to using inspection.
Merge conflict in whats_new.rst
Merge pull request #3006 from ogrisel/fix-implicit-init-introspection

[MRG] FIX: more robust skip of implicit constructor
MAINT don't use Perl in Makefile when sed suffices

Also replaced xargs with find's own command execution. This is more
robust in the face of paths with whitespace in them.
ENH: Refactoring and optimisation of sparsfuncs.pyx
ENH: Optimise sparsefuncs
a] Removed numpy overhead in finding mean
b] Removed enumerate
c] Added tests to test_sparsefuncs
d] Replaced multiple looping with a single loop
Moved sparsefuncs to sparsefuncs_fast