Correlation in python | اردو میں سیکھیں

#statistics #baba_aammar #python #dataScience
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[@Codanics]

Like this video and comment you name with timestamp.

[@aasimnawaz]

thanks codanics
#positive, negative , zero, slightyly positive, slightly negative
# pie chart etc

[@amnafarooq5871]

Amna Farooq ., Completed .. In this video the importance of correlation and correlation with Python is described on two type of Datasets:Titanic and Iris. Conditions of Positive , negative and No-correlation is described by regression plot and heat map.

[@SaleemKhan-vv3ks]

Great job

[@ishratfatima1570]

started watching

[@faizali1830]

completed ,... Thanks #Codanics

[@sabazainab1524]

My thesis is to find statistical dependent patterns from the dataset for which we use correlation to figure out which variables are dependent on each other which will actually give results in the form of patterns but I have to implement the exact formulas of these tests on the basis of type of data and considering the assumptions. I hope I easily will be able to work on it.

[@MuhammadArslan-dz9fi]

# covariance with respect rows
cov_mat = np.stack((kashti['age'], kashti['fare']), axis = 1)
print(np.cov(cov_mat))

[@faizaafzal121]

start watching

[@Reality11075]

after corelation how we select feature automatically mean hm istrah code write krany k wo automatically corelation sa acha feture separate kr da

[@faizali1830]

03:21 Faiz Ali

[@Reality11075]

question yee ha k hm generally knsa features drop krna hn higly corelated (positive or negative)

[@zuhaibkhan3862]

0:17 Zuhaib A. Khan

[@adenrajput8531]

0:00 INTRODUCTION
2:45 Covariance
3:40 Importing Libraries
8:48 Correlation
12:58 Regression plots
16:21 Heat maps
18:53 pair plots
2:31 scipy correlation

[@usmanayaz4617]

8:09 Usman Ayaz

[@MuhammadArslan-dz9fi]

# covariance with respect columns
cov_mat = np.stack((kashti['age'], kashti['fare'] ), axis = 0)
print(np.cov(cov_mat))

[@251wardahrasheed7]

Did it work for you ? I am getting the nan values through this code.

[@fozailkhan5672]

0:00 INTRODUCTION
2:45 Covariance
3:40 Importing Libraries
8:48 Correlation
12:58 Regression plots
16:21 Heat maps
18:53 pair plots
2:31 scipy correlation
Dataset used: 'titanic', 'iris', 'penguins'

[@waqasahmad8170]

waqas ahmad 10:55 ..start watching

[@luqmanbutt9335]

Muhammad Luqman

[@meharunnisa8706]

Mehar-un-Nisa, completed this video 23:09

[@rizwanakhan5007]

0:48 oil instea of petrol

[@lala_minate]

Name: Ali Haider
Date: 07/23/2022
Time 3:45 pm

[@mohsinkhalid9597]

Petrol khna tha oil kh dya

[@randomx1818]

Baba jee, explain properly, if sepal length increase what will be the consequences, what effect will be on petal length.. You didn’t justify properly the relationship of both the features evenly.
Moreover, i think you just plot the features correlation... Explain in it what terms conditions should be occurs so far when you have to drop the features bcz this is to be very important aspect in terms ML modelling.
“Share the whole dataset not samples”

[@asfandyarsaeed6402]

Sir Bab G is not going through a case study in this case he is educating us how to use these things. what you are asking is related to the case study please watch other future videos to get this answer 🙂

[@usmankhawaja8711]

started watching

[@muhammadwasimkhan116]

02:05:00 Correlation...?