best work bro...One doubt i am having if able to clarify it would be helpful. In Iris data set with these code X = iris.data y = iris.target feature_names = iris.feature_names target_names = iris.target_names
how it has taken Feature names: ['sepal length (cm)','sepal width (cm)', 'petal length (cm)','petal width (cm)'] Target names: ['setosa' 'versicolor' 'virginica']
Hi pa, Please use the below code you will see the results. import pandas as pd import numpy as np from sklearn.datasets import load_iris iris = load_iris() print ("FeatureNames:",iris.feature_names) print ("TargerNames:",iris.target_names)
Bro na data analysis and data visualization mudichan ...na indha playlist ah next follow pannanum ah illa ...machine learning algorithms follow pannanum ah
beginners ku idha vida theliva puriya weika mudiyadhu. thanks for your clear explainations bro, from sri lanka
Sir, Your teaching methodology with indepth knowledge is ultimate so easy to understand. You can train anyone. YES. Great.
Thanking you for this wonderful videos, I'm beginner to this field. Your videos helping me lot. Excepting more videos sir.
Hii
Did you find any other option to learn machine learning??
If any, can you tell me about it .
All the best
One of the best videos in my life
🙏
King of machine learning 👏👏👏
Thank you suriya prakash reaching our channel
hi really awesome work, keep posting the lectures
Thank you sure
Super bro...neyeraya video podunga bro
Bro vera level la solithariga and idhu mathiri yarum solithara mataga
Thanks ajay
Excellent work 👍
Puriyamalam Ila bro very clear. Ah puriuthu thankyou for ur effort. Bro kadamaiku soli tharama clear ah explain pandringa
Thanks 🙏
Its very explanation bro.... Kindly post more number of case studies
Sure pa!
Excellent bro.
Sir unga videos Ku oru road map Sollunka sir, before machine learning playlist shall we watch data analyst play list?
I will post one shorts about playlist how to approach it
Nice explanation.
Good work Bro. Great Service. I admire your attitude and wish you the best of luck. ..Stay safe and be blessed.
Thank you Rajkumar😀
Good Work sir keep it up
Keep watching
And data analysis roleku ML playlist fulla ah padikanuma or skitlearn matum enough thaana bro
bro really amazing work.... y did u stop posting videos for last 2 months.. please post continues videos ... and unsupervised algorithm
Thanks pa...started posting again..
Amazing tutorial
Thanks gopal
Data analysis roles unga data analysis playlist with some tool enough ah but dataanalaysis unga python basics ila bro
Aama...python pathi videos podala...bro...in future la add panure..
👍good job
pudichiruku bro
romba thanks na
Keep supporting!
Bro machine learning enna library padikanum bro
Basic libraries therinju vachukoonga...code Pannu pothu demand iruntha ena library venum o atha kaathu konga namala elame napakam vachika mudiyathu bro..
best work bro...One doubt i am having if able to clarify it would be helpful.
In Iris data set
with these code
X = iris.data
y = iris.target
feature_names = iris.feature_names
target_names = iris.target_names
how it has taken
Feature names: ['sepal length (cm)','sepal width (cm)',
'petal length (cm)','petal width (cm)']
Target names: ['setosa' 'versicolor' 'virginica']
Hi pa, Please use the below code you will see the results.
import pandas as pd
import numpy as np
from sklearn.datasets import load_iris
iris = load_iris()
print ("FeatureNames:",iris.feature_names)
print ("TargerNames:",iris.target_names)
@@lwm-4501 thanks brother
Nice
Bro na data analysis and data visualization mudichan ...na indha playlist ah next follow pannanum ah illa ...machine learning algorithms follow pannanum ah
Yes bro atha follow up pannunga
Super bro
Thanks nithya share with your friends
நிங்க அந்த டாக் வச்சு அந்த module run panninga எல்லோருக்கும் புரியும். matarix யை வச்சு முதல்ல அரம்பிச்ச குழப்பத்தில் முடியும். நன்றி
Thanks for your feedback
👍
Bro enakku sariya puriyala😢 pls explain pannunga bro🙏🏻