[Hindi] Linear Regression Code In Python Sklearn! - Machine Learning Tutorials In Hindi

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#Code import matplotlib.pyplot as plt import numpy as np from sklearn import datasets, linear_model from sklearn.metrics import mean_squared_error diabetes = datasets.load_diabetes() diabetes_X = diabetes.data diabetes_X_train = diabetes_X[:-30] diabetes_X_test = diabetes_X[-30:] diabetes_y_train = diabetes.target[:-30] diabetes_y_test = diabetes.target[-30:] model = linear_model.LinearRegression() model.fit(diabetes_X_train, diabetes_y_train) diabetes_y_predicted = model.predict(diabetes_X_test) print("Mean squared error is: ", mean_squared_error(diabetes_y_test, diabetes_y_predicted)) print("Weights: ", model.coef_) print("Intercept: ", model.intercept_) # plt.scatter(diabetes_X_test, diabetes_y_test) # plt.plot(diabetes_X_test, diabetes_y_predicted) # # plt.show() # Mean squared error is: 3035.0601152912695 # Weights: [941.43097333] # Intercept: 153.39713623331698

[@rafayjangsher762]

I have a little confusion that why we are slicing? Is it the same concept of sample and population in statistics?

[@nomadindiagaming11]

Sir ye series complete ho gyi kya?

[@manishsharma2211]

@@rafayjangsher762 that is nothing bus splitting into train and test datasets

[@taha2279]

sir can u please telll me that y your mean square error is so high bcz it means that it is very poor model

[@visheshraval6119]

@@taha2279 no , in video sir wrote model.fit(diabetes_X_train, diabetes_X_train) by mistake , it should be model.fit(diabetes_X_train, diabetes_y_train) see in second parameter "Y" should there

[@MohitK96]

This level of teaching at free of cost is great....

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first of all thank you, sir, for explaining such an easy explanation, I tried many online platforms but found this very useful. kindly sir complete the series by at least covering most of ml algorithm along with code plz

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Mere liye ye bhoot motivation vala part rahega ki appke video main 965 subscribe hain aur abbhi dekh raha hun ki 6 million se zyada subscribes hain.❤

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Bahut hi badiya tarika tha linear regression with multiple features explain karneka plus the code part , honestly you have taken way the fear of machine learning , I found this video equally motivated to learn machine learning. Thanks mere Bhai !

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awesome yaar you are very energetic keep it up and one thing in this video that during code don't show yourself 10:17 because we can lose concentrate but when you want to talk then show yourself during code with distrube us don't mind it is a point i see that

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[@Vaibhav20x09]

Harry bhaia , I think that for the first 30 elements, we should type [ : 30] while [ : -30 ] will take elements from starting and will end at the last 30th element

[@niteshprajapat7918]

exactly , I was too confused. why -ve sign was used

[@jayati6693]

same, I checked that again and again, last 30 elements should be diabetes_X[-30 : ] and as you said first 30 is [:30]

[@rajkumardongre3085]

Actually Harry bahi is talking last 30 elements for test and rest is for training therefore : test = diabetes[ : -30] i.e test is a set from 1st element to last 30 elements. train = diabetes[-30 : ] i.e train is a set of last 30 elements I hope now you have a clear idea

[@prashinparikh2199]

@@rajkumardongre3085 I am not able to plot scatter plot why? Its giving me value error

[@rajkumardongre3085]

@@prashinparikh2199 Make sure the length of diabetes_X_test and diabetes_y_test are same(i.e 30). you can use len(diabetes_X_test) to find the length of diabetes_X_test. I hope this might help you

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harry bhai you are amazing ! very easily u explained it. thanku

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Thank you so much harry sir, you really teach very Nicely and love your videos and i have learned a lot

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It is the responsibility of the academic of the viewers to like, share and subscribe to the channel as the teacher is delivering the lecture and we are going to perform our responsibility as a virtue.

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Thanks for sharing all good work. My question is that How can I add confidence intervals in codes and plots as well. I think in that case I’ll have three predicted cases.

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25:32 bhaiya ekdum santusht hain!! thanku very much!!

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Simply wowww... great explaination 👍👍 and thanks a lot for the code.

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Empathy word ko samjhte ho bhai tum......sahi mae bahut ache video hain.

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Amazing. An immense thanks to you...

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from 965 subscriber only to now almost 5 million subs, this is what real dedication looks like

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Wonderful explanation 💯 and then very well explained coding part...Thanks

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very very nice ....uh made d complex things very simple...thanks

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I don't know how to thank you bhaiya....... lots of love to your channel

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is that a TVS Gold keyboard... ahh old style love. those mech keys sounds so soothing to ear.

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Very nice broo keep it up , but upload all videos as soon as possible thnx for the explanation ,Gbu broo

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Without your explanation I wouldn't have learnt machine learning 😊

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Sir Ji, you are best as always.

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I keep it bro ur teaching style is best .. pls bro complete the course of machine learning i need it

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You have done a marvelous job...

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Dheere dheere apke bi lakho subscriber honge . Bhai ap mehnat and achai ka kam kr rhe ho isliye apko thoda time lgega.

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Oh my God 😱 I just saw that he has only 965 subscribers at the time of making this video he don't even know that in future he will cross 1 million Love you code with Harry 🎉🎉

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exactly brother , just in few yrs. This is because of his way of teaching, hard work, joking

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Now he's near to 4 M

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appreciated ...harry sir ...keep going...

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love u bro ,thank you so much for all ur efforrts

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Bhai u r a blessing 🙏😇

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Bhai app see best koi nahi sikha sakhta

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Sir best series ever.

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Thanku so much sir..for amazing playlists..I am little be late..but wo khate hai na der aaye durshat aaye..

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Your completely hard wok, we every one get a lot benefit - thank you. I.A.Siddiqui Karachi

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journey from 965 to 2M . content is power congratulation harry

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Your my guru of coding

[@vishleshumberkar63]

Hi Harry, Good to see all the concepts simplified. however, just one question, why we have used pycharm here, and why not Jupyter Notebook.

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impressive way of teaching👍

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The journey begins from 965 subscriber to 3.6 million subscriber hats off harry bhai 🔥🔥🔥

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hello Herry Sir I am requesting tutorials on tweets sentiment analysis by using scikit learn. Generation word cloud of negative and positive comments, how to prepare training data etc. I love your tutorials. they are just great.

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Mst kaam harry bhai

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thank you so much for ML series It helps me a lot

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You are great sir

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thank you bro my exams are near but now I cleared many doubts from your video

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Congrats for 1K......

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Excellent bro...keep it up ...

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Great job .... awesome.. Please make video on Time Series analysis and prediction

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Great resource still relevant.

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Great teachings sir

[@jinglerobs1]

Nice video sir, please could you advise how to plot graphs with multiple features