Register and get free Certificate for the course: glacad.me/3tq4Tp2 The following topics are covered in the session: * Introduction - 00:00:00 * Case Study to understand the need of Linear Regression - 00:01:12 * Introduction to Linear Regression - 00:04:18 * Introduction to Multiple Linear Regression - 00:09:49 * Simple Demo in R and Python - 00:11:00 * Comprehensive explanation of Linear Regression Algorithm - 00:35:47
Only thing issue i have gone through i was not able to see the white board's contact as well as projectors contacts . Although i have tried to listen sirs word and tried to understand . If this issue could be minimise than i think this course will be the best course .As the explanation of sir was outstanding . ❤️❤️❤️
Thank god I found this video. Such an awesome explanation. I learned a lot from this video. A very big thank you sir. Professors like you are very rare to find.
Hi, thank you for all your support and appreciation. Your support motivates us to deliver such valuable content. Stay tuned for more such informative videos on our TH-cam channel:)
My name is najiib and i am from somalia this the best course of linear regression i seen even i teach during my machine learn course but it wase difficult for me to understand linear regression but i am now understood more thank you great learn you help me lot and also i will thank the professor 🥰
Rao sir you are superb- All we had learnt in school that y = mx + c don't ask why put the value and get the answer 90 percent in exam, parents are happy but students like me lost intrest cause of why we are doing how this values coming, Thank you very much you all are doing the best work on the earth. #Respect you all.
Hi @Siddharth, your appreciation means a lot to us. We are glad that our video has helped you and we will continue providing all these informative videos. Thank you and keep supporting us:)
This is the best tutorial. Respected Mukesh Sir explained it the way may be none else can(not disrespectful to other great tutors). Thank you great learning team for making this amazing available for all of us. Guys can you upload the second part also of this great session?
Hi @Anushka, thank you for your appreciation and we are happy to help you. We also have live sessions that happen every day, you can join with us and all your doubts will be cleared there and then. You can check all the details on our community posts and also register yourself. Thank You
Hi @Raiza, don't worry we have a solution for you, if you wish to do the full course on Data Science for free along with the assignments, course material and certificate, then check this link: glacad.me/FreeCourses_1000Hours . Also, do subscribe to our channel for more videos like these. Thank You
You have very good understanding of concept i request you to please make some more videos and contribute the community, Again you are genious, Try to learn ML but due to lack of statics concept having some difficulties, I tried books but still in trouble, Your video made me so comfortable. i appriciate what you are doing.
Thanks a lot. We are glad you found our video helpful. We are working on creating a lot more content for learners like you. Meanwhile, do not forget to subscribe to our channel so that you get notified whenever we upload a new tutorial.
Thanks for these videos. Just a suggestion: for key topics like Linear models, Time series analysis, Multivariate statistical analysis, Optimization, etc, perhaps you could create two videos, one at an elementary level and another at a more advanced level (for people who have the linear algebra and statistical inference background). I know you don't want the courses to become too theoretical but the latter type of videos will definitely appeal to engineers, physicists, economists and others who want to make a jump into data science or ML.
Excellent way of teaching, very focused on the topic yet simple. Has made me understand the concepts very well linking all the required topics, explaining why, what and how
Thank you so much, glad we could help😀 Subscribe to our channel for more such content, and hit the bell icon so you are always notified of updates from us!
very nice video it is very useful for the students who cannot spend much money for studying in top classes very useful for us thank you great learning for such a videos please update more videos for us to study and learn more things
Thank you so much for your kind words. We will be uploading more videos like these regularly. Please do subscribe to our channel and click on the bell icon so that you get a notification of our new videos
We are glad you found our video helpful. If you want to also do assessments and projects along with learning the course please visit and enroll for the free course on Linear regression, here: glacad.me/GLA_linear_python If you complete the courses and the assessments here you will also get a certificate of completion.
Glad you think so! We regularly post such informative content, so subscribe to our channel NOW and hit the bell icon so that you never miss an update from us😇
Thank you for sharing this lecture. This is very helpful. Around 2:17:41, professor shared a link to refer about linear regression assumptions. Could you please share that link?
2:15:27 , the scatter plot should have been labeled residuals vs predictions , that plot should not show any trend ideally(homoscedastic assumption ) , whereas the plot of actual y values vs predicted y values should show a linear trend indicating the y predicted and actual are same and model has performed well
Thank You for your feedback. We'll look into it. If you want to also do assessments and projects along with learning the course please visit and enroll for the free course on Stats for ML here: www.greatlearning.in/academy/learn-for-free/courses/statistics-for-machine-learning If you complete the courses and the assessments here you will also get a certificate of completion. Hope this is helpful.
Your request has been noted. We are working on creating a lot more content for learners like you. Meanwhile, do not forget to subscribe to our channel so that you get notified whenever we upload a new tutorial.
If we are changing the slope(m) for gradient descent for best fit line. Then why we have to find the m value at first place...? we can directly vary the m value starting from 0.1 and check for the best fit line? can someone explain
Dear Learner, Kindly register at the following link:www.mygreatlearning.com/pg-program-artificial-intelligence-course?ambassador_code=GLYT_DES_Middle_SEP22&GLYT&GLYT_DES_Middle_SEP54
If the residuals are not normally distributed, this would mean that the model is not able to fully explain the data. Hence, it would be better if you go ahead with some other model than the current one.
Hey bro, can you help me out with from sklearn.linear_model import LinearRegression? I get an error message from using. This is the error message I'm getting. from R and python.ModuleNotFoundError Traceback (most recent call last) in () ----> 1 from sklearn.Linear_model import LinearRegression 2 regressor = LinearRegression() 3 regressor.fit(X_train, y_train) ModuleNotFoundError: No module named 'sklearn.Linear_model' Thanks bro.
Sir what is the difference in drawing multiple lines randomly and drawing 3 lines and minimising the error both the things are same, how can we say that those line which have minimum error would he best fit line, as we draw infinite lines we can draw infinite line and try to minimize the error.there is no difference
Hey, when you talk about minimizing the error, you would have to change the angle of the line and this would give you a new line entirely. The best line is one such line which would have the least error when compared with all other lines.
@@greatlearning so draw infinite lines and then compare it from best fit line, isn't it difficult to compare, we draw infinite line comparing each and every line from best fit line which one has minimum error, its illogical.
Prof Mukesh Rao is Academic Director for Data Science at Great Learning. Hope you found his teachings useful. Please do subscribe to our channel to see more content.
Hi, Unfortunately we can not provide code here. But, don't worry we are always here to help you. If you do this course on our website for free, you will get all the course material and also certificate on completion, here is the link to check: glacad.me/GLA_linear_python. Also, don't forget to subscribe for more videos like these. Thank you:)
Thanks for your suggestion! We'll plan to create such content in the future. Meanwhile, explore our TH-cam channel for more content in Hindi. www.youtube.com/@greatlearning
Get the certificate of completion for the course on Linear Regression for Free: glacad.me/3cBQXSU Also to access the datasets, projects, assessments, and codes, register on Great Learning Academy. You can also enroll for any of our 80+ courses offering 1000+ hours of content for free
Great Learning I have completed this course fully over here on TH-cam, when I go to claim my Certificate, it says I have to do all the modules again, any other way out, where I can directly jump to the quiz and claim my certificate.
Register and get free Certificate for the course: glacad.me/3tq4Tp2
The following topics are covered in the session:
* Introduction - 00:00:00
* Case Study to understand the need of Linear Regression - 00:01:12
* Introduction to Linear Regression - 00:04:18
* Introduction to Multiple Linear Regression - 00:09:49
* Simple Demo in R and Python - 00:11:00
* Comprehensive explanation of Linear Regression Algorithm - 00:35:47
1:07:20 "Don't worry about the formulas, get the concepts in place" - summarizes the mantra for anyone willing to learn Data Science.
Only thing issue i have gone through i was not able to see the white board's contact as well as projectors contacts . Although i have tried to listen sirs word and tried to understand . If this issue could be minimise than i think this course will be the best course .As the explanation of sir was outstanding . ❤️❤️❤️
Thank god I found this video. Such an awesome explanation. I learned a lot from this video. A very big thank you sir. Professors like you are very rare to find.
Hi, thank you for all your support and appreciation. Your support motivates us to deliver such valuable content. Stay tuned for more such informative videos on our TH-cam channel:)
My name is najiib and i am from somalia this the best course of linear regression i seen even i teach during my machine learn course but it wase difficult for me to understand linear regression but i am now understood more thank you great learn you help me lot and also i will thank the professor 🥰
Rao sir you are superb- All we had learnt in school that y = mx + c don't ask why put the value and get the answer 90 percent in exam, parents are happy but students like me lost intrest cause of why we are doing how this values coming, Thank you very much you all are doing the best work on the earth. #Respect you all.
Hi @Siddharth, your appreciation means a lot to us. We are glad that our video has helped you and we will continue providing all these informative videos. Thank you and keep supporting us:)
This is really called we got something in free no ADS, Thanks a lot for your contribution.
This is the best tutorial. Respected Mukesh Sir explained it the way may be none else can(not disrespectful to other great tutors).
Thank you great learning team for making this amazing available for all of us. Guys can you upload the second part also of this great session?
This professor is good at explaining , thumbs up.
Thanks for the appreciation. Please do share the video and subscribe to our channel so that you get a notification of our upcoming videos
The best explanation And answers to all my questions solved so beautifully. Seriously, Thank You for these set of videos, keep coming up with more. ❤️
Hi @Anushka, thank you for your appreciation and we are happy to help you. We also have live sessions that happen every day, you can join with us and all your doubts will be cleared there and then. You can check all the details on our community posts and also register yourself. Thank You
Etne Dino se Kaha the Prabhu aap? 🙏🔥
Thank you so much 😊
if my teacher would have taught me like that in school. i would have been a data scientist in High School
Hi @Raiza, don't worry we have a solution for you, if you wish to do the full course on Data Science for free along with the assignments, course material and certificate, then check this link: glacad.me/FreeCourses_1000Hours . Also, do subscribe to our channel for more videos like these. Thank You
Majority of our issues and lack of interest stems from the teachers and their weak grasp of the subjects been taught.
Budget is one of the major factors for this.
Great Explanation and now I am clear with the concept. Indeed great learning. kudos
You have very good understanding of concept i request you to please make some more videos and contribute the community, Again you are genious, Try to learn ML but due to lack of statics concept having some difficulties, I tried books but still in trouble, Your video made me so comfortable. i appriciate what you are doing.
Very good Teacher ,1 of the best i have seen ,want more from him for us
Thanks a lot. We are glad you found our video helpful. We are working on creating a lot more content for learners like you. Meanwhile, do not forget to subscribe to our channel so that you get notified whenever we upload a new tutorial.
I am just so grateful for this lecture. It explains a lot of ambiguities and I am glad that most of them has been sorted out. Thank you
This was an awesome lecture- thank you , sir has incredible understanding of the subject :)
Bharani sir the way you speak, teach are amazing
Thank you sir 🙏🏻🎀
Thanks a lot. We are glad you found our video helpful.
Just an awesome lecture, better than paid lectures.
Thanks for these videos. Just a suggestion: for key topics like Linear models, Time series analysis, Multivariate statistical analysis, Optimization, etc, perhaps you could create two videos, one at an elementary level and another at a more advanced level (for people who have the linear algebra and statistical inference background). I know you don't want the courses to become too theoretical but the latter type of videos will definitely appeal to engineers, physicists, economists and others who want to make a jump into data science or ML.
Thank You for your suggestion, we'll keep that in mind.
Crisp and clear. Execellent delivery sir. Thanks lots to the the team greatlearning. I would happily suggest to the students who are in need of.
Amazing way of explaining. I learned easily with the help of this video.
Excellent way of teaching, very focused on the topic yet simple. Has made me understand the concepts very well linking all the required topics, explaining why, what and how
Thank you so much, glad we could help😀 Subscribe to our channel for more such content, and hit the bell icon so you are always notified of updates from us!
thanku so much sir ,from your vedio all my concepts are clear
Really, I learned a lot from this video. he cleared all concepts. Thank you so much sir for giving such a wonderful knowledge.
very nice video it is very useful for the students who cannot spend much money for studying in top classes very useful for us thank you great learning for such a videos please update more videos for us to study and learn more things
Thank you so much for your kind words. We will be uploading more videos like these regularly. Please do subscribe to our channel and click on the bell icon so that you get a notification of our new videos
Best explanation and 💯 best teacher ever 💯
Thank you. Please do share the video :)
one word for him : GENIOUS.
Fabulous really...thank you dear professor
Hi we are glad that you liked our Content Please do subscribe to our Channel for Similar & Awesome Content
Very good and deep explanation, but it would be better for learners if you provide direct link for datasets and code files for exploration.
We are glad you found our video helpful.
If you want to also do assessments and projects along with learning the course please visit and enroll for the free course on Linear regression, here: glacad.me/GLA_linear_python
If you complete the courses and the assessments here you will also get a certificate of completion.
i just love baharani sir . can u make series of all the lecture of Baharani sir
?
Hello! Bharani sir is working on more content. Do subscribe to our channel so that you get notified whenever we upload a new tutorial.
:)
HAT'S OFF for your explanation sir
Glad you think so! We regularly post such informative content, so subscribe to our channel NOW and hit the bell icon so that you never miss an update from us😇
Thanks for free lectures
nice explanation. could He use a better board marker? it's sometimes difficult to look at what he's writting in the white board
We'll keep that in mind
Thank you for sharing this lecture. This is very helpful. Around 2:17:41, professor shared a link to refer about linear regression assumptions. Could you please share that link?
best teacher ever
Hi we are glad that you liked our Content Please do subscribe to our Channel for Similar & Awesome Content
2:15:27 , the scatter plot should have been labeled residuals vs predictions , that plot should not show any trend ideally(homoscedastic assumption ) , whereas the plot of actual y values vs predicted y values should show a linear trend
indicating the y predicted and actual are same and model has performed well
Please correct the subtitles
fantastic material
Much more getting help in clearing concepts
@Great Learning, Will it be possible to provide the Link, Professor mentioned at 2:17:54 ?
Teacher keeps great experience
Glad you think so!
Please make the video in Hindi for Linear Regression, Logistics regression,
Linear
Regression
Logistic Regression
Classification
Clusterings..
there is another video in Hindi by this title Linear Regression in Hindi
Absolute bliss
Great lecture. But the visibility of the white board is very low. Can you please provide the PPT part.
Thank You for your feedback. We'll look into it.
If you want to also do assessments and projects along with learning the course please visit and enroll for the free course on Stats for ML here: www.greatlearning.in/academy/learn-for-free/courses/statistics-for-machine-learning
If you complete the courses and the assessments here you will also get a certificate of completion. Hope this is helpful.
I wish theyd shown the workbook past 3 hrs much more. There was a lot of code that wasnt shown.
Please add videos on Graphical algorithms
Your request has been noted. We are working on creating a lot more content for learners like you. Meanwhile, do not forget to subscribe to our channel so that you get notified whenever we upload a new tutorial.
super professor best explanations..
Thanks for the appreciation. Please do share the video and subscribe to our channel
If we are changing the slope(m) for gradient descent for best fit line. Then why we have to find the m value at first place...? we can directly vary the m value starting from 0.1 and check for the best fit line? can someone explain
Where to buy/access all lectures of this teacher? Please guide.
Dear Learner,
Kindly register at the following link:www.mygreatlearning.com/pg-program-artificial-intelligence-course?ambassador_code=GLYT_DES_Middle_SEP22&GLYT&GLYT_DES_Middle_SEP54
@@greatlearning Okay Thanks.. And where is next lecture of this youtube lecture?
Great but would like to have that code if possible
very insightful
Why residuals should be normally distributed in linear regression algorithm? What to do if this assumption would not hold good?
If the residuals are not normally distributed, this would mean that the model is not able to fully explain the data. Hence, it would be better if you go ahead with some other model than the current one.
This lecture required the pre-requisite knowledge of r programming??
Hey, yes! For the demo part, you would require knowledge of R programming.
I can not find the dataset using the link ?
I’m a student of finance..Is this same for Ecnometrics subject ?
How can we find the intercept and slope here
Hi sir, can you provide placements with free course?
Share the links that are in presentation
i need the ppt of this lecture ASAP
plsss
how can we get the data that you were using in the tutorial to apply hands on
Projector screen and board not visible clearly, please more close focus on screen and board.
Thank you for your feedback we'll look into it
can anybody please share the website that the professor mentions in 00:02:18
Hey bro, can you help me out with from sklearn.linear_model import LinearRegression? I get an error message from using.
This is the error message I'm getting. from R and python.ModuleNotFoundError Traceback (most recent call last)
in ()
----> 1 from sklearn.Linear_model import LinearRegression
2 regressor = LinearRegression()
3 regressor.fit(X_train, y_train)
ModuleNotFoundError: No module named 'sklearn.Linear_model'
Thanks bro.
For male female what to use instead of 0 and 1. I couldnt make out
Sir what is the difference in drawing multiple lines randomly and drawing 3 lines and minimising the error both the things are same, how can we say that those line which have minimum error would he best fit line, as we draw infinite lines we can draw infinite line and try to minimize the error.there is no difference
Hey, when you talk about minimizing the error, you would have to change the angle of the line and this would give you a new line entirely. The best line is one such line which would have the least error when compared with all other lines.
@@greatlearning so draw infinite lines and then compare it from best fit line, isn't it difficult to compare, we draw infinite line comparing each and every line from best fit line which one has minimum error, its illogical.
Can someone tell in which online institution can i find this lecturer?
Prof Mukesh Rao is Academic Director for Data Science at Great Learning. Hope you found his teachings useful. Please do subscribe to our channel to see more content.
read the captions at 0:16
Hii can i get this ipynb file of linear regression?
I wish if programming section used Matlab. What does cgpa and gre stand for?
CGPA is the grade point average of the student and gre stands for the GRE score of the student
@@greatlearning Thank you sir and greetings from Algeria
Can you please share the code
Hi, Unfortunately we can not provide code here. But, don't worry we are always here to help you. If you do this course on our website for free, you will get all the course material and also certificate on completion, here is the link to check: glacad.me/GLA_linear_python. Also, don't forget to subscribe for more videos like these. Thank you:)
🔥🔥
in hindi🤩
Thanks for your suggestion! We'll plan to create such content in the future. Meanwhile, explore our TH-cam channel for more content in Hindi. www.youtube.com/@greatlearning
Need subtitle!😥
We are working on that and soon it will be available.
@@greatlearning thanks🙏🏻👍
We can't see anything on the whiteboard
Not so great learning when you can't even see what's being written on the board.
Get the certificate of completion for the course on Linear Regression for Free: glacad.me/3cBQXSU
Also to access the datasets, projects, assessments, and codes, register on Great Learning Academy.
You can also enroll for any of our 80+ courses offering 1000+ hours of content for free
Great Learning I have completed this course fully over here on TH-cam, when I go to claim my Certificate, it says I have to do all the modules again, any other way out, where I can directly jump to the quiz and claim my certificate.