Sky CH. Wang skychwang

##Perks of Microsoft

####Salary

####Health and Wellness Care

Medical and hospitalization: Two choices for medical insurance. Both with no premium but different deductibles.
- The two choices on medical plans are a high-deductible health plan (Microsoft puts a chunk of money into the Health Savings Account for you, which covers most of the deductible) and an HMO.
With the HMO, you pay basically nothing as long as you only go to Group Health doctors. With the high-deductible plan, you're covered under the local Blue Cross provider which means you can go to just about any doctor in the country. For


	from keras import backend as K, initializers, regularizers, constraints
	from keras.engine.topology import Layer


	def dot_product(x, kernel):
	"""
	Wrapper for dot product operation, in order to be compatible with both
	Theano and Tensorflow
	Args:

	def dot_product(x, kernel):
	"""
	Wrapper for dot product operation, in order to be compatible with both
	Theano and Tensorflow
	Args:
	x (): input
	kernel (): weights
	Returns:
	"""
	if K.backend() == 'tensorflow':

	def smart_procrustes_align_gensim(base_embed, other_embed, words=None):
	"""
	Original script: https://gist.github.com/quadrismegistus/09a93e219a6ffc4f216fb85235535faf
	Procrustes align two gensim word2vec models (to allow for comparison between same word across models).
	Code ported from HistWords <https://github.com/williamleif/histwords> by William Hamilton <[email protected]>.

	First, intersect the vocabularies (see `intersection_align_gensim` documentation).
	Then do the alignment on the other_embed model.
	Replace the other_embed model's syn0 and syn0norm numpy matrices with the aligned version.
	Return other_embed.