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Linear Regression Practical Implementation In Hindi

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Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable's value is called the independent variable.
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Опубликовано:

28 авг 2024

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Комментарии : 117

@ParthPatel-db4tk Год назад

fit_transform() is used on the training data to learn the scaling or transformation parameters and then applies the same transformation to the training data. transform() is used on new data (e.g. test data) to apply the same transformation that was learned on the training data.

@ritikkohad5045 Год назад

Thanks brother

@ayushpant8290 Год назад

thanks bro

@kartiknampalliwar8603 5 месяцев назад

i am unable to do first step i.e load_ boston is showing error can you please help me

@dhmahbub 4 месяца назад

@@kartiknampalliwar8603 that data is not available in the new version. You can alternatively use "fetch_california_housing" and load it. Probably that is the similar sort of data.

@hiteshkotian6023 3 месяца назад

@@kartiknampalliwar8603 load_boston is no longer available use some other data like load_diabetes or something

@SubhashKumar-ek2tm 2 месяца назад

fit_transform is used on training data to learn parameters and transform it, while transform is used on new or unseen data to apply previously learned transformations without re-learning the parameters.

@talhagalaria571 2 года назад

fit transform and transform = we want to keep as a surprise is no longer unknown to our model and we will not get a good estimate of how our model is performing on the test (unseen) data which is the ultimate goal of building a model using machine learning algorithm.

@patelkdhawal 2 года назад

Can you elaborate more. Please

@user-yl5dg2gc8c 11 месяцев назад

playlist ke hisab se video dalo sir, theory aur practical implementation ke video mein bahot fark hai , much samjh nhi aya, r2 score, cross validation , xtrain ye sab kya hai theory mein to that he nhi ye sab.

@Techwithgalvan 5 месяцев назад

yoo bhai

@luckythecutepie Год назад

fit transform is used in train data set to predict the value(linear regression) test data set just to se our accuracy with the model.

@meetsaurabhtiwari 6 месяцев назад

Sir , your effort is really wonderfull and is inspiration. please make a separate playlist for EDA and feature engineering , lakhs of aspirants are wait , please make it on serious note.

@avinashmirchandani8731 2 года назад

Please more videos on machine learning also practical video more Thankyou

@TuneTube312 Месяц назад

Thank you sir 🙏

@Aman-yu4re 3 месяца назад

Do I need to know sklearn before starting this playlist ?

@pratishzaware1430 2 года назад

Nicely taught the algorithm..Thanks for making learning simple

@MrPravinsoni 9 месяцев назад

Boston housing dataset has been removed from scikit-learn. Is there any way to load it as a bunch data??

@ubarbde 6 месяцев назад

from sklearn.datasets import fetch_california_housing housing = fetch_california_housing()

@user-ns2xy1uw6d 3 месяца назад

from sklearn.datasets import fetch_california_housing use this

@anujgupta328 3 месяца назад

Gradient decent iss implementation mein kaise implement kaise hua?? Agar back end mein hua toh alpha value kaha diya?? @krish please explain

@sonalikamble5929 2 месяца назад

Great thank you

@cybermascot Год назад

problem with the inbuilt datasets is that they are removed often later when new versions is released, like Boston dataset is no more part of sklearn in-built dataset. it would be great if you use independent datasets in future.

@ayushmangupta6682 11 месяцев назад

There is any way to download the boston dataset with the dependent feature I want to implement the linear regression if there is any way please suggest

@shivanshmishra8395 10 месяцев назад

Ya its a problem i am facing as well

@EjazUddin786 5 месяцев назад

@@shivanshmishra8395 have got solution how to import please let us know to help

@AbhijeetDewangan-gr9sj 5 месяцев назад

@@ayushmangupta6682 please use " from sklearn.datasets import fetch_california_housing " alternative of Boston

@shrunkhalawankhede2611 2 дня назад

Same problem

@Gattu_g 2 года назад

Sir you explain soo good please continue making videos in hindi

@roshanbhattad4493 13 дней назад

boston dataset is removed from sklearn

@xyz3588 4 месяца назад

sir sklearn na dataset remove kar deya ha. dataset fetch nahi ho raha ha

@neeshantn9742 2 года назад

Great video sir...just one concern...Why we are not checking VIF?

@Sachin-xj1oq 3 месяца назад

Can anyone please explain displot discussed in this video?

@jaydodhiawala4117 Год назад

sklearn removed load_boston which dataset i can use to follow along?

@krishnaikhindi Год назад

Fetchcaliforniadataset

@dnswm95 10 месяцев назад

@@krishnaikhindican we use fetch_california_housing ??

@faheemsyed9481 4 месяца назад

great job sir jee

@kishormagar3160 2 года назад

Very good Sir

@alirathore6818 2 года назад

why are we using 'neg_mean_squared_error' can u please share link linear regression loss function video ?

@user-dx9ml2wf4q 3 месяца назад

where is the theory playlist? can someone please attach the link in the reply to this comment

@toufique3390 2 месяца назад

too complex🙁

@jatinjoshi1830 Год назад

Thank You

@sauravsahay8803 4 месяца назад

How is it that you are predicting on x_test but calling your y_test as truth value?

@anilmurmu6675 2 года назад

What value of MSE , RMSE, R-square should be taken into consideration to come to conclusion that model build is accurate one? Is there any range of value for MSE, RMSE and R-square ?

@aftab6417 Год назад

R2 to be gerater than .70 that is 70%

@yadnyeshkhotre2001 Год назад

boston dataset is been reomved from the kcikit liberary

@azharafridi9619 Год назад

which one do you use right now. facing the same problem bro

@aishwaryajadhav8736 Год назад

same issue @@azharafridi9619

@Prachi_Gupta_zeal Год назад

what is random state= 42 in that train test split command?

@shashankmokashi1406 2 года назад

Good video sir.

@satyamghule147 11 месяцев назад

i use the same model on 'fetch_california_housing' dataset and the mse i got is 0.5.

@shivanshmishra8395 10 месяцев назад

Me too.. and the score is 0.34

@bhuvansagar3294 8 месяцев назад

same, and as mentioned by the other person, my score is 0.33

@yamrajoli3834 6 месяцев назад

I am seeing you videos just to similary apply another multivarite problem but when I got the displot(with kind=kde) it came similar but of the rang eof the 1e^9 so How can decrease the error should I use the tunning or what ?

@visshalgupta Год назад

Sir i didnt able to understand what is y the dependent variable . I mean which column is gettimg predicted ?

@Yash_Patil. Год назад

bcoz we evaluate our model on test data set

@NavyaTrilokD 3 месяца назад

But what are we predicting here? Can someone explain please..what does the values in "reg_pred" tell us? what is the difference between values in target features array and "reg_pred" values?

@NavyaTrilokD 3 месяца назад

so we are predicting the output feature house pricing...for the independent features in x_test, dependent feature or actual values are in y_test. After applying linear regression, predicted values are in reg_pred. In linear regression we find the difference between actual values and predicted values, that is the error. MSE is that error here.

@ajaykushwaha-je6mw 2 года назад

Sir please l1 and L2 k liye bhi video banaiye

@vikasvachheta7135 Год назад

*** please create EDA and Feature engineering playlist in HINDI ***

@manchalamani9475 Год назад

Sir this can be explain in English language some what difficult to understand Hindi

@rakibulislamrabbi373 5 месяцев назад

Sir the boston dataset is no more available in the scikit-learn datasets also can't load the boston dataset in juyter notebook can U please provide any solution for that?

@innocentgamer8670 5 месяцев назад

you can use the alternate dataset like california housing , or you can search and save the boston dataset , and use pd.read_csv() method to use that dataset

@AbhijeetDewangan-gr9sj 5 месяцев назад

please use " from sklearn.datasets import fetch_california_housing " alternative of Boston

@nileshnaik3111 2 года назад

nice video sir

@nileshkshatriya5827 2 года назад

Please keep uploading videos in hindi

@datasciencegyan5145 2 года назад

Krish ap kon sa video software use kerto ho recording k liye

@MnB_music 2 года назад

Simply amazing ❤

@moghalkarishma2378 9 месяцев назад

here linear regression doing but why taken independent features more than 1 feature can anybody tell me

@swapnilkulat5990 Год назад

The Boston datasathas been removed from sklearn....

@brahmadevrai4369 2 года назад

Sir when new batch start for data science?

@lakshyajain7435 Год назад

Kuch samajh nahi aa raha...

@BEEAnkitgupta 9 месяцев назад

sir if my accuracy_score is 0.85 then my predication model is good or bad?

@paraguchbagle6413 3 месяца назад

bouncer ho gya ye video

@harshsrivastava1662 Год назад

kind='kde' not showing that graph

@Gangstersongs125 3 месяца назад

Sir in this where us accuracy

@sowmyavvasu84 9 месяцев назад

Sir i have build the model in linear regression and performance of evaluation metrics are also done. Now additional I want to add one more new row(instance) and find the performance of it how to do can you guide me pl. How to check the performance particularly that single row.

@filmybeats4827 9 месяцев назад

Bro I couldn't understand this to that level how can I understand these concepts as sir is directly implemented it so

@abhinavbm3338 Год назад

what is score?

@dheerajgupta3805 Год назад

subscribed

@ajaykushwaha4233 2 года назад

How to know model is overfitted or stable model.

@entertainmenthub7700 2 года назад

if it perfectly fits to the traning data in simple meanings if it remember the data instead of learning it overfits

@tusharsalunkhe7916 Год назад

Why Y_train is not standardized? Please answer

@satyamghule147 11 месяцев назад

Standardization is typically applied to the feature variables (X_train) rather than the target variable (Y_train) in machine learning.

@AmitSharma-oh5uw 6 месяцев назад

sir ap dataset bhi dal diya kro. load_boston to ho ni rha hai hmara. kaise kre ab

@niharikakhanna3585 6 месяцев назад

same problem, kuch solution mila?

@AmitSharma-oh5uw 6 месяцев назад

@kakhanna3585 hi niharika are you a data science student. pehle mene socha inke 38 videos hi hai machine learning ke. and me bhut jldi complete kr lunga. but me 2 video se age hi bdha hi ni abhi tk. ye beginers jaise ni pdha rhe hai. and mujhe ek ek chiz likhna pd rha hai, ki sir kya bol rhe hai video me. and wo atleast definations bhi likhwate to smjne me easy hota. it's difficult to understand. kya apko koi aur playlist pta hai. jisse jo machine learning ke liye ho.

@piyushff3258 27 дней назад

use fetch_california_housing class alternative of boston

@hannahvm8044 Год назад

Plz do videos in English🥲

@adila8128 11 месяцев назад

If you're looking for videos in English you can refer to his other channel. You will find all the videos in the English language.

@B.D.M1999 6 месяцев назад

load boston has been removed

@AbhijeetDewangan-gr9sj 5 месяцев назад

please use " from sklearn.datasets import fetch_california_housing " alternative of Boston

@user-iq1yw9bz6f 5 месяцев назад

Bhai fetch wali BHI Nahi Chal rahi

@m.laxminarayanreddy 2 года назад

i got a score of "0.017460452225004253" why i got low score?

@himanchalpawar167 Год назад

Same prob

@__________________________6910 2 года назад

Noice

@HoneySingh-cu3pw 6 месяцев назад

Esi video bnaya naa kro jo kisi k leptop m work naa kre kya jya oerte ho smj nhi atta padhne bethq toh sara dinak khrab ho gya kuch hua nhi

@self_official Год назад

sir aap JSPM Tathwade ke student hai kya

@trojanhorse8278 8 месяцев назад

youtube shanel

@JagFi Год назад

Boston housing dataset has been removed from scikit-learn. Is there any way to load it as a bunch data??

@ausking3081 8 месяцев назад

import pandas as pd import numpy as np data_url = "lib.stat.cmu.edu/datasets/boston" raw_df = pd.read_csv(data_url, sep="\s+", skiprows=22, header=None) data = np.hstack([raw_df.values[::2, :], raw_df.values[1::2, :2]]) target = raw_df.values[1::2, 2] or install version 1.0.1 pip install scikit-learn==1.0.1