#44 Naive Bayes Classifier With Example |ML|
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- čas přidán 27. 08. 2024
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Thank you very much mam
Easy to understand your teaching 😊👍
A😅😅
Mam we have exam on 24th JNTUH....please try to cover topics from other units also...atleast complete 3rd unit....we'll have chances to pass atleast then....thank you so much for covering all the topics from last two units☺
haa s
Oh oh divya 😄😄
@@maheshadhimulam3074
Mahesh anna topper
did you pass the exam or do you still dance?
Mee class lo teachers chappara papa
Thanks mam...for absolutely explain....i got so deeply 🙏💕
I think I'm watching first youtuber videos where I don't need to speed up the video, it's naturally too fast & quite interesting. :)
Thank you ma'am it was a very well explanation of naive Bayes... could you please share the lecture on brute force Bayesian algorithm and good links regarding these lectures
00:02 Naive Bayes Classifier is a classification technique
01:07 Understanding the definition of the Naive Bayes classifier
02:22 Naive Bayes Classifier is used for classification in machine learning.
03:29 Understanding the calculation process in Naive Bayes classifier
04:22 Using multiplication to calculate the probability of events
05:04 Naive Bayes classifier uses probability to make predictions.
06:47 Naive Bayes Classifier with Example
07:29 Naive Bayes Classifier is used for investment classification.
Mam I have ml sem exam on 24th of this month ...I request to make info covering atleast 3 chapter .. thankyou ❤️🙏
Thank you so much mam its very helpful and clear explanation. Please cover the other topics in 4,5 units also madam
You are Genius! Love from Ireland. I am doing MSC in AI here and your tutorials help me get clear concepts.
Mam, then what is the difference between bayes optimal classifier and naive bayes classifier?
Thanks alot ma'am ....May god bless you 🌹❤️
computational learning theory--introduction,probably learning an approximately correct hypothesis......sample complexicity for finite and infinite hypothesis space......the mistake bound modei of learning
instance based learning--------introduction,k-nearest neighbour algorithm....locally weighted regression....radical basic fn,cases based reasoning,remarks on lazy and eager learning
plz make videos on this topics...plz.
thankyu soo much for your notes.....well explained...and the rest of the topics left in this unit make videos on-- bayesian belief networks,the EM algorithm.
I am not understand how the total value is 650 but what you are told is totally confused
Because in the classes yellow, sweet, long they are repeated
Mam this is unfair you put the thumbnail of your image but in video , no facevideo of yours 🙁
You are here for the face ?😂
@@shaikaftabahmed9666 maybe😅
@@shaikaftabahmed9666bro got click baited😂
Pass tho karna bhaiii
Kyu nahi ho rhi pdai
UNIT - III
Bayesian learning - Introduction, Bayes theorem, Bayes theorem and concept learning, Maximum
Likelihood and least squared error hypotheses, maximum likelihood hypotheses for predicting
probabilities, minimum description length principle, Bayes optimal classifier, Gibs algorithm, Naïve
Bayes classifier, an example: learning to classify text, Bayesian belief networks, the EM algorithm.
Computational learning theory - Introduction, probably learning an approximately correct hypothesis,
sample complexity for finite hypothesis space, sample complexity for infinite hypothesis spaces, the
mistake bound model of learning.
Instance-Based Learning- Introduction, k-nearest neighbour algorithm, locally weighted regression,
radial basis functions, case-based reasoning, remarks on lazy and eager learning.
Excuse me Ma'm U deserve more views and likes according to your quality of content.
I wish that 2024 will bring more views 😊😊😊😊😊😊😊😊
Mam In exam we can write any example or they will give table? because in spectrum and most of cases example depends on enjoy sports but ,You explained fruit example and some youtubers explained other examples please answer my question
Thank you for your efforts
Mam I have exam on 3rd sep...so please do more vedios as soon as possible 😌
I don't know who are you but thanks a lot you saved my 5marks
You have such a beautiful voice. ❤️
all glories to u saved ma lyf
This is a best presentation but i face one difficulty that is madam speaking speed is fast. and i am face difficulty to understand a complete sentense. may be my processor is old one and madam processor is very fast as well as modern
Mam plz upload more all topic videos atleast upto 4th unit I have exam on agus 24th jntuh
You saved my day!!
your voice iz choooooooo chweeeeeeeet uWu😍😍😍😍
Well explained thank you mam
its completely understood mam ... i have small doubt y are the total oranges are 650 i did not understand that
This is because there can be oranges which can be both yellow & sweet...i.e. each fruit can have multiple features (yellow, sweet & long)associated with it.
Mam can u explain SVM IN MACHINE LEARNING
what resources do you use for learning??
Please teach again with another example
Shouldn't we multiply by P(Orange) while calculating P(Fruit = Orange)? and divide by the product of prob of Yellow, Sweet and Long?
What is the difference between naive Bayes and Bayes optimal and Bayes theoremmm......all are looking same please post crct videos ...
Can u pls provide the implementation part...i mean how to implement it in code
Mam in this example why you are considering denominator
And mam please share your notes also
They are very clear and easy to understand
Tq mam
Plz do some more vedios of continuation topics of ML
Thanks mam for the video
Good afternoon madam
I have exams
Jntuh
Pls post all topices about the
Machine learning
Nice 👍
akka assal hyderabad lo akkaduntav akka vachi prase chestha
Is naive base classifier and naive base models are same..shall i write in exam
Mam but in data set we have more no of data items,here u just taken 3-4 data items.For a data set how should we do that 👉👈
Mam please cover upto unit 5
On 24 th we have ML exam
JNTUH
Thanj you mam
Future mam
thank you so much
ty & ily
In the fruit example the first row is total 800 na
Why the total is not same for rows and columns mam
Mam make playlist on embedded Systems mam
Thanks madam
Thanks
Tqs madam
In 6:00 you’ve made a mistake. The probability of fruit being orange is not 0. However, if you said the probability of orange being sweet AND yellow AND long, then the answer is 0.
Thank you
You're welcome
So for total we should take a random whole number????
Hii mam we have different topics in second module in 6th sem can u teach us
Analytical learning plz
How can total no. Of oranges are less than no.of yellow oranges+no.if sweet oranges??
Because an orange which is yellow can be sweet as well. That's the property of independence of the attributes
Total of long is wrong it is 85
What about examples that is Bayesian belief network
Hole total ia also wrong
Mera kal exam hai 7 jan 2023 ko
Mam I can't understand how you calculated total number of fruits
Please respond
Machine learning exam on 24th Aug
Jntuh
Mam, the total orange fruits is 800,but you wrote 650,how?
Noo total is 650 only she explained it in the video in the beginning.
i was a great explanation but the total of above example is wrong , the total fruits will be 2050
No bro you calculate coloum wise
Our ML exam is on 22nd ... We are JNTUH students Make all the units as fast as possible... Please help us
On 24th august *
@@mawabro8574Ela rasav bro 😂
Mam we have exam on jan 2022
didi i cleared accenture cognitive test and also my both the codes were executed successfully on 16 august when should i expect communication assessment and interview ?? plz help 🙏🙏🙏😕
Create your own content instead of copying from others
Done
can you please look after your voice its bit too low while playing the video
Please give me update about final remainder accenture mail
why dont u complete the full problem
Mam exam on 24 so please complete ml video series atleast on/before 24 aug mam
I’ll try
Oka mukka ardam kalyy asalu laste 3 line topic 😢
Long one
We want notes sister can u provide plz😢
i am getting irritated from this subject
why u always take the same example of the 5-min engineering videos?
350+450=800 how it's come 650 meam please
Tell me that logic
do videos on compiler design ......
Go and listen akka education 4u😂😂😂😂
you have taken the example in wrong way mam and you took the total also wrong you didnt even explain y should take that values plz explain it clearly
Y r u in 2x
ichipadesavv!!!!!!!!!!
maam it is absolutely unnecessary to do all this formulation
copied from 5 minute engineering🤣🤣
MADAM TOTAL GALAT AARA HAI,ITNE CHAANTE MAARUNGA ITNE CHAANTE MAARUNGA
if you are not comfortable in english then tere is no shame in explaining in hindi in my opinion
I guess she doesn't know Hindi,her mother tongue is Telugu...
ganda intro, please change
Video ki starting m ye cartoon vala music kyu lga rkha... Aadha mood to isko sunker hi khraab hojata