Now let's build a pipeline for preprocessing the numerical attributes:

#1

I did not understand the pipeline topic.

from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler

num_pipeline = Pipeline([
(‘imputer’, SimpleImputer(strategy=“median”)),
(‘attribs_adder’, CombinedAttributesAdder()),
(‘std_scaler’, StandardScaler()),
])

housing_num_tr = num_pipeline.fit_transform(housing_num)

I did not underrstand the whole.

help me to understand it.

#2

did not understand.

Why did we take imputer why not others??

Why attibutes adder??

I saw the video but i did not understand much.

Please explain these two.

#3

cat_pipeline = Pipeline([
(‘selector’, DataFrameSelector(cat_attribs)),
(‘cat_encoder’, CategoricalEncoder(encoding=“onehot-dense”)),
])

I did not understand what is the work of selector??

What is the work of cat encoder.

Please explain these two,

#4

Could you please give me a time when we can schedule a time sometime next week so that we can understand the issue better over a Hangout chat? Thanks.

#5

Can we talk here ??

just asking…

#6

I will sehedule but after 8th december because i am going to merrige ceremony.

Is it possible to talk after 8th december??

Please reply.

#7

Please send us an email to reachus@cloudxlab.com whenever you have time and we can talk to you over Hangout like we did the last time. Thanks.