Tutorial 25- Probability Density function and CDF- EDA-Data Science
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- Опубліковано 28 лис 2019
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The way you explain concepts is amazing.
you are an awesome teacher; seems like completely dwelling over the concepts... simply i take a bow
Man you do not know how much i learned from you , your explanation is AWESOME
Krish loves the word PARTICULAR a ton! 😁
PRETTY MUCH too :)
Institution of Data science claims that they have good content for freshers also but it is no there, i always have to come in your channel for many topics clarification which I could never learn from there.
You have a great skill of teaching😊
Thanks for sharing sir, I always admire your teaching style, knowledge and helping nature. Small clarification, in normality plot, values on y-axis does not tell us area under the curve. In this way, y-axis corresponding to mean value on the x-axis will always be .5 but that is not the case. Actually, it is the gradient value of the CDF function (graph).
Thanks Krish for sharing your knowledge. Please keep it going.
you are much better than many online courses in market ...thank you please keep going.
thanks your series is great , u made this very easy.
best explanation of cdf when compared with other youtube videos.
Simply explained. Good going Krish.
He explained two topics in less than 10 minutes, yet its so clear and informative
The y-axis of pdf is gradient of cdf, the higher the gradients, more the density is at that particular point. The y-axis of CDF is the percentage population of a particular point.
Yes, that is what I'm thinking but in the video it creates some confusion.
this comment should be pinned...... It creates lot of confusion for those who don't about this
Thank you for clarifying these functions.
Feeling amazing with Krish Naik!
Most simplest and non-confusing video on PDF & CDF. Thank you for the same.
But sir, when I plot KDE plots with seaborn, I often get the values on the y-axis more than 1. What the interpretation will be then? Or KDE plots are different from Density Curves?
Thank you. I like your teaching style!
Simply amazing explanation 😍😍
Thanks alot and keep doing sir!!!
One of best video of PDF and CDF..thanks sir
Sir, i have a problem regarding installation of anaconda. After installation when i launch jupyter notebook, on the top of the bar it shows kernel error as a result of which the code doesn't run. So, what should i do to overcome this error?
Buenos!
Do you have videos of real cases showing inferential statistics to test (validate) models?
Thanks for the video sir, I learned lot of things in this video
thank u so much . god bless u
Excellent !! Very nice explanation.
Well explained, Thanks a lot Krish.
When you explain the PDF, you said, it is the area under the curve till that point. I think this is the CDF, not PDF. Thanks a lot for your effort nd videos
that is correct...he is probably talking about CDF
A query,then how do you interpret a pdf?
i think krishna sir had explain it right.
@@madhuprasath6193 It basically gives you the probability of that point. PDF would answer a question like these:- What would be the chance of weight of a person to be 90kg?. Answer to this as per the above graph in the video would be "only 25% chance ( or 0.25 probability )". Basically PDF tells us the exact probability for every point.
area under the curve in particular (definite integral) range is pdf:: total must be unity
Thanks to wonderfull video..............i will simply add through pdf we can find the probababilty for a point or a range whereas cdf tell about the less than probability
learning about machine learning for google spreadsheets, this helped understand the CDF so much thank!
Too many clear concepts in just 7 minutes !!! Thanks man!!
hello are you also trying to learn data analysis?
Why do we calculate CDF as PDF is already giving you % of distribution for required data analysis, through this CDF, we are getting added (C.values) but what is the significance of this concept?
Amazing video sir. Thank you so much.
Thanks for this video Krish.
We will be very happy to see atleast a single reply to any comments in youtube as well as issues in his github.
I usually see the comments and make a note on it to create videos...github videos will be coming up soon
@@krishnaik06 Thank you Krishna. Waiting to see your updates.
@@krishnaik06 sir what is benefits of cdf over pdf ? bcoz we will be analysing same precentage with pdf also.
awesome video sir! thank you!
Good going Sir keep up the good work :)
Thank you sir .. the way you explain is so easy to understand...
Krish pls provide you're online course registration link
Hi krish, kindly let me know pls explain how do you say at point 130 in X axis with 90% in distribution in Y axis is "less than" since the CDF is straight it is increasing and you are mentioning less than 130kg is there in 90% of the dataset. How do you predict it is less or high using CDF?
this video is a soul saver
so is CDF simply a another representation of a PDF , just wondering at what point do you decide to use a CDF over a PDF if it simply represents data in a different way ? it seems like the CDF always locks the results between 1-0 . what if the returns go -Negative how would you represent that ? Thanks as always .
very well brother your are great teachning
Sir please make a video on navie byes algorithm.
In 3.08 you mentioned that the y-axis in the normal distribution represents the % of distribution below that point. If that statement holds true then shouldn't the graph be continuously increasing and it would be cdf? So what does the y-axis indicate for the normal distribution falling in the right half? Please correct me if I am mistaken, but would like to understand this better.
y axis shows the %age distribution of intervals
Ty sir your video was really helpful..👍
dont you think the cumulative total will go above 1? at 3rd 4th value itself ?as the probabilities are getting added ?
Great explanation krish😊 .please make video on practical implementation of this concepts using python.
Crystal Clear!
Simply amazing i read so many articles on cdf but everyone was calculating the value no one explained it so well can I plzz connect you on LinkedIn
Your explanation is too good bro
nice videos thanks krish naik sir
sir PDF it using KDF but for CDF which is function running background?
Very informative video....can you suggest some simpler kaggle datasets on which we can perform EDA using PDF,CDF and multivariate analysis. I have already done on iris, Titanic and Haberman's dataset, but was thinking about getting more practice.
hello pretty friend
thank you for the video
Can you suggest how can I plot a CDF using distplot in seaborn?
thankyou sir.
Very good explanation.
Hi Krish, thank you so much, I speak Spanish but I understand you, I really need an explanation of this topic and I don't found in Spanish, you're great bro
If data is not in form of gaussian distribution then the pdf or cdf will work or not
Excellent explanation of PDF and CDF
Sir is this subject exploratory data analysis and statistics subject the same sir please reply 🙏
As far as I know CDF is Cumulative Distribution function. It can also be calculated for Probability Mass Function. But you can say in this Scenario as Cumulative Distribution function of given Probability Density Function.
We can use logistics regression right based upon cdf ?
Hi Sir,
where can we study the mathematics behind all of the ML algorithms
NPTEL its the best. start with that if you want to go deeper then probably start with advanced statistics
Excellent !
Sir, your explanation is amazing ^_^
Thank you !!
how will calculate the above 60% in pdf and how will take the cumulative percentage in cdf give with mathematical explanation sir
Thank you sir ♥️
what if cdf over a period of time is not being constant and hits 90 degree and then goes constant, why is that straightline coming in cdf?
Hi sir. Thanks for sharing awsome content like this. I have 1 question. Can we calculate percentile and median from CDF?
hai krish , ur vedios are really helping me to learn machine learning very easily , can u please upload svm and xg boost vedios please its a request
I've commented on your other videos also, there I understood the love you had on the technology. From this video I understood that, actually you're so much passionate on teaching sir. The way you explained PDF and CDF is really amazing sir. Thank you so much. :)
Hello sir
In some videos values in y-axis of pdf is referred as probability for a point on x-axis . I am bit confused can you please explain.
Really it's an awesome explanation.
No, one cannot define probability at a single point x for a continuous random variable. It should always be a range
Why is PDF differentiated and how area under the graph gives us probability..
Amazing...plz make a video on how to determine the distribution of a dataset using Python.
Can you please show the practical implement of PDF and CDF
Thanks for the video Krish. But I do have a doubt that in a long run.. how could be it will be beneficial that this much percentage of data lies upto certain threshold?
outlier detection perhaps
amazing video
sir may u please make video on hypothesis.
you are the best
Small correction - Probability cannot go over 1 , but probability density function can go.
Correct me if I am wrong
what is the formulae for smoothening the histogram?
best explanation
Nice one
Nice explanation
Nice 😁 could u do a comparison about survival function, inf and all other methods please
If you are smoothening the curve, why count changes to percentage of distribution.
Very nice 👌.
Can pdf be greater than 1 in Z distribution
What scenarios we will use CDF and PDF in machine learning..?
I have the same query. Can you please give any domain specific example and show is how PDF and CDF curves will help the data scientist to take certain decisions..
yeah ..same query me too
Don't know its application in ML yet, Since I have started learning recently but one use of it is in EDA
Which is the exploratory data analysis.Exploratory means you don't know anything about the data set from before. Your task is to extract some basic yet critical information about the dataset before implementing ML algorithms.Its important to get an idea about the dataset .PDF, CDF various plots such as 2D, pair plot , etc are some aspects of EDA.There are other stuff also.You can google it to understand more .
Amazing :)
Good explanation
Hi
You have used only weight one feature to determine pdf n CDf can we do with two or more features
Great question, expecting answer from any DS enthusiast
no, its univariate analysis
Sir the analysis which we do with CDF, we can do the same with z-score. Am I right?
CDF is a general concept, applying to all sorts of distributions. Z-score is limited to normal distributions.
Why do I need to use this distribution ? In which cases of data it's helpful ? Also we have uniform distribution, binomial and poisson. Where to use these. Appreciate if practical examples are included. Great explanation with graphs. Keep up the enthusias,
elite explanation, gg
Krish is the God of data science
Your god for me now😮
Sir , how can I code it?
can you please explain about T-score and T distribution