Tutorial 22-Univariate, Bivariate and Multivariate Analysis- Part1 (EDA)-Data Science
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Ur teaching is little bit hard...m unable to understand in a proper way...I always want to see ur videos but when it starts.. after some time ..m exhausted
True
you should see statistics playlist and some idea about ml to understand
Hello Krish sir, the determination you have in making videos, that's commendable.
Sir ,Kindly revert data preprocessing videos..Because it was removed ..pls ..and upload overfitting and underfitting oriented real time program explanation ...thank u very much ..
Is it helpful to MBA RESEARCH METHODOLOGY AND STATISTIC ANALYSIS??
U are the life saver I have already explored many many videos related to data science and ML and all of your videos are very understandable and go straight to the points . Thanks youtube and Krish Naik for such great tutos.
Krish Naik, I want to understand multivariate analysis better, and I found your tutorial 22 was excellent, you are a great presenter, perfect English, amazingly clear method of exploring the analysis problem with histograms, etc. But then I found tutorial 23 was recorded badly, so I could not understand your voice easily. I clicked on subscription, and heard you talking at length about your services (again, recording not clear), but most of it was not relevant to my specific need. Why can't you just show a price list of specific items? This could include little items like "how to do multivariate analysis" , or "how to do bivariate analysis", or "How to join our 6-month course to be a data scientists" , each with a price. But I am not prepared to join, just because you are an excellent teacher. I am a customer, and I want what is useful to me right now, not your views on a long-term relationship that may, or may not, be useful. But thank you for tutorial 22, and good luck.
I am impressed with your energy and sound knowledge of your subjects. I always look out for your you tube video for detailed explanations. keep it up
thank you so much....waiting 2nd part☺️
Hi Krish, I have one doubt with respect to Pre Data Processing techniques. I know it is very difficult to generalize but could you please suggest the most common Pre - Data Processing techniques. I'm not sure if it is a candidate for one of your videos.
I am new to the channel. I'm taking statistics courses in college right now and these videos are very helpful with making things easier to understand. Thank you. Subscribed
sir after a person is certified data scientist what are the other things he should learn to boost his career.
If you are interested in business, I would suggest getting a CFA or FRM(Meanwhile, keep improving your skills in ML). By applying advanced machine learning techniques, you are probably able to make unintuitively valuable suggestions and extrapolations, which worth some money. (easy 250k annual compensation)
I guess you should use word multivariable as you are using one dependant variable,in case of multivariant there are more than one target variables
How can be one so much talented..
Great explanation..
You are very energetic . I randomly clicked this video, but ended up subscribing this channel..
Hi krish please add compleat oops concept videos
One of the best teachers out there
So who is your favorite teacher in your place of study other than krish?
Something that no one usually mentions but took me a while to grasp is that a high correlation between your output and indep. variable/feature is good for your model, but correlation between 1 indep. variable with another one is not great for model, and it's in that case where we need to work with them.
I'm sorry but you are a Confusionist sir.. Teaching is not for you. Please start writing Text books
you have introduced too much outlying information. kindly stick to the topic.
Which part of the video made you to comment this? Please let me know
Which one is the best addon for getting more opportunities as a fresher in IT industry as a datascientist with higher salary option?
*Elective Bundle-1*
NLP with ML
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multivariate normality in assumptions and multivariate analysis are same
soo confusing
Quick question here, where do we use univariate analysis then?
When we use these method before cleaning the date or after cleaning
when "you should not see a 4 d diagram":-()
Hi, hope you're doing well.
Sorry I have a question.
Is there any multivariate dataset in the internet that the variables are labeled?!!!!!
As far as I've checked the multivariate dataset that I've seen, are labeled based on observations( for example observation 1 suffer from cancer, 2 do not and....)
Now I want the variables have lables.
Is there any data set?
I'll be bery thankfull if you help me.
Thanks in advance🌸
Hi Sir
Could you please make a video about BI services
plots used for multivariate analysis like PCA, PCoA and NMDS, CCA any video on that?
sir can you send the this videos playist link plz sir
so useful and clear, saved me a lot of confused wikipedia surfing :)
Big misunderstanding here! Regressing over multiple features to fit one response/independent variable is called UNIVARIATE multi-VARIABLE regression.
Good useful video now i grasp the basic of how to apply the ML algorithm
Practical example is required..waiting for next part..
awesome explanation as always! thank you so much Krish!
Great video. I have a problem related to the topic which I want some help with. Can anyone answer which one is correct and little explanation on how to solve it? Here is the problem:
There is an email marketing template and we want to replace it with a better template. A is the control template. We also test email templates B, C, D, and E. We send 100,000 emails of each template to different random users. We want to figure out what email gets the highest click-through rate. Template A gets 10% click-through rate(CTR). B gets 7% CTR. C gets 8.5% CTR. D gets 12% and E gets 14% CTR. We want to run our multivariate test till we get 95% confidence in a conclusion.
Which of the following is true:
a) E is better than A with over 95% confidence. B is worse than A with over 95% confidence. You need to run the test for longer to tell where C and D compare to A with 95% confidence
b) Both D and E are better than A with 95% confidence. Both B and C are worse than A with over 95% confidence
c) We have too little data to conclude that A is better or worse than any other template with 95% confidence
Krish : Amazing lecture ..you are making me understand the fundamental of statistics so easily.. god bless you.
thank you .but please join me as member
Can take univariate for single input features and multivariate for multilabel classification in NLP?
you are great bro .. thanks . very useful.. w8 for more video with lots of examples : ) thnk
Hi Krish, I'm seeing this video a bit late. But many things with respect to Uni and Multi variate analysis have become clear to me. Thanks Krish!!!
literally
well explained the fundamentals of ML
Sir what is mentioned in y axis grsph of univariate analysis how that number came??
Thank you for making these informative videos. Being a student of data science your videos are gem and you are the asset to students learning the subject! Please keep uploading! Thanks
Thanks much Kris. Feature = variable. May you just do away with Y-component and only have horizontal line for weight. That is consistent with saying there is no Y component on Uni-variate analysis.
in class what ever they explianed for 3 hrs, you could tell that in 15 minutes .. Content is too good ...
This is the first ever time i am commenting on some video bcz i couln't resist .
Krish, I am iNeuron student .. and I must say so beautifully you have explained this topics with a lot of clarity ... TY
whats name software open source on windows?
Your explanation is easy to catch. Worth listening. Accent is good. Giving the basic things along with really helps. Pliz keep doing this thing.. thank you
you are a good speaker. Things to be corrected in video -> sigmoid function is non linear! hence logistic regression is non linear. Svm as you mentioned is not a non linear classifier and it is a linear classifier.
sir app best teacher ho bohot acha samaj aata hai appse plz keep sharing your knowledge with us and we will support you and learn new concepts of data science
Excellent sir 👍👌
While discussing univariate analysis why you put data on -Ve and +Ve measure even you haven't talk about it
Hi Krish
U r doing great work. Would you please suggest some resources to understand probability and linear algebra resources.
Please refer Statistics for Management by Richard I Levin and David Rubin
@@mcbhuva007 any TH-cam channels
Thank you for the video. It’s clearly explained.
good explanation sir
Very nice explanation sir✨✌🏻💯❤
How age and DOB are different features?
Very good work. Looking forward to next part
Logistic regression could have polynomial feature and many different features
I have progressed so much in short time following your tutorials. I hope one day to get a job of a data scientist.
What are the parameters for univariate/bivariate/multivariate Gaussian models?
Sir can I ask a question what makes multivariate statistics similar from univariate or bivariate statistics
Please
, how to perform EDA on dataset with many one hot encoded features??
Can you please let me know about Bivariate Demand
Hi Krish, thanks a lot for your help, I have been learning a lot from you. Just wanted to know if you have a video that explains high-level end to end DS projects. I saw one that you had for Feature Engineering and wanted to know if you have one for the whole process?
what is the difference between regression analysis and path analysis
Hi Krish, Why you have taken negative values the Y-axis ?
How do I do these analyses with categorial variables?
i regret that i underestimated you and your channel when i came across many times before. Sorry I judged the book by it's cover :( Thank you so much.
I dont understand, how do people retain all this information.
thanks for give us for video brother. keep it up.
What if i have categorical data and want to plot a heat map/pair plot
Convert ino numerical and then plot
Where is the playlist sir
Very useful tutorial. Thanks for uploading this tutorial.
Are Pairplot / correlation matrix - bivariate or Multivariate?
I need an explanation of uni-variate data analysis
Is excel also used in data analytics?
Yes
I was searching for this kind of video since a long time... value overloaded....Thank you krish for your wonderful content.
Is this a dance Class ?
thank you
Amazing, Thank you for making it very clear.
Sir Hindi me padhadete 😅
Sir could you please also explain multivariate analysis in time series
Not good explanation
Hi,
Please share the link of playlist of explanatory data analysis
First
Very much easily understandable sir
7:00 multivariate
thank you sir
Thank you sir
easy to understand way of teaching.
Sir, Is it permissible to perform multivariate analysis using the k-nn algorithm?
Hi suur
I want to ask how to avoid overfitting.. Know that I used dropout(0.5) and data augmentation with fine tuning
Please, any help!!
Kindly use Ridge regression ( run Cross validation to take mimnum Lambda value and plug it in Ridge regression). kindly check "stat quest" channel on this topic
@@kadhirn4792 thank u, I'll search for it
I have another question, since u r here😊😁
I want to get features extracted by an object detector model like RCNN or Yolo of a dataset, and then use these features for classification
Is that possible? If it is, please any help or guidance!!
@@abdellahgrinzou548 Not much idea on CNN
@@kadhirn4792 okay, thanks a lot 😁
Keep sharing us, u r doing such a great job. God protect you 😊
Thank u sir for the valuable class
you explain so well. thanks,
Please explain Cox regression analysis
Sir ye research methodology ka h
thanks
dude. you are good at teaching
Good work bhai, best wishes.