Softer testing methodologies unit - 3, path and path products applications .jntuh syllabus .we have exam on 28 Aug. Can you please do a vedio on this topic plz?
Mam I am sharing u our 3rd chapter syllabus: please cover the leftover topics ... Pls mam Convergence and local maxima Representation power of feed forward networks Hypothesis space sreach and inductive bias Hidden layer representation Generalization Overfitting Stopping criterion And an example - face recognition
Sister shrinking coefficients with detailed algorithm and example...please do video on that... Sem exam undhi akka fast ga chesi pettava....Please understand sister
Mam I am sharing u our 3rd chapter syllabus: please cover the leftover topics ... Pls mam Convergence and local maxima Representation power of feed forward networks Hypothesis space sreach and inductive bias Hidden layer representation Generalization Overfitting Stopping criterion And an example - face recognition
too complicated when there's only 1day left for exams and you have just started
Me literally watching this 3 hours before the exam 😂
If you watch this topic before exam then no word to say rather than RIP bro 🤣🤣🤣
I have 2 hrs left for exam. I still have 3 chapters left but I m still in 1st chapter
Atleast you start before a day
Myself start before an hour for exam
@@miniminni7114 tbhi cg nhi aa rhi
Thank you! I wandered on internet for hours to understand Backpropogation. Your 3 videos made it simple like a cake. Amazing
Tq very much for this ML playlist
By this way till the time of my exam I can be able to learn maximum topics from syllabus..
You’re welcome all the best for your exam
Such a great 😃 playlist but this 3 video are out of my mind!!!
i surrender 😂😂😂
I am present only for part 1 and part 2😂😂
But need to appreciate for your efforts ma'am
I'm gonna leave this question. There's no way I can complete this even if I get 3 hours lmao.
Fckn truth 🤣
I like only for your effort and hard work ❤❤.
Full confusion 3 part, my mind is absent
hahahahahahaaaa....... I just love this kind of jokes...... 😂😂😂😂😂
Can you mention the updated weights of w6,w7,w8
Softer testing methodologies unit - 3, path and path products applications .jntuh syllabus .we have exam on 28 Aug. Can you please do a vedio on this topic plz?
I just understand "Hatch 1" Tommorow is my exam 😫
Mam I am sharing u our 3rd chapter syllabus: please cover the leftover topics ... Pls mam
Convergence and local maxima
Representation power of feed forward networks
Hypothesis space sreach and inductive bias
Hidden layer representation
Generalization
Overfitting
Stopping criterion
And an example - face recognition
Mam do u have videos on deep learning by ian Goodfellow
You are great mam✨✨✨✨✨
my exam will be on 23 this month.please post all the playlist of our jntuh syllabus as soon as possible.atleast 1st 3 chapters
Yeah I’ll
Post Question paper i have exam tomorrow
Jntuh
Very nicely and clearly explained....
what is threshold value?
Thank you so much 💜💜
Will this method need any change if the activation function changes?
Can you please Upload a Video on Derivation of Backpropagation Rule
learning rate "n" is it a constant or it will give in question
Thanks you mam,your explanation is very good
Thank you mam 💞💞💞💞💞💖💖💖💖
Sister shrinking coefficients with detailed algorithm and example...please do video on that... Sem exam undhi akka fast ga chesi pettava....Please understand sister
Mam how to find n value
U are substituting n value how do i get.....
mam, can u pls drop formulas for w6,w7,w8,w2,w3,w4
thanku so much didi
Mam can you please explain occams razor topic..
i just wasted my 2 crucial hours to learn it(exam night)....bt all are out of my mind now🥲🥲
3:31 I think you did a mistake here, when we exchange the denominators, it will be E/out x net/net. Do look into this.
And thanks for the efforts ❤️.
you are entirely wrong go check your math again
Can you prepare videos for Artificial Intelligence
Thank you so much for your kind efforts maam!!
Thank you
Automatic differentiation in gradient calculus
Mam , plzz drop the formulas for w2,w3,w4 🙏
can you olease drop the formulas for w2 w3 w4 an in part 2 w6 w7 w8 please just the formulas
🥺
Heloo mam I'm from kalasalingam university can u plz post on cnn problem mam i have exam on 20th November 2023
U teaching superb mam on back propagation
Did you complete this sum fully? If yes can you share the answer ?
can you pease explain feed forward networks and multilayer perception
I have exam tomorrow
nalla malla reddy
p. vineeth
vimp questions
of ml
A W E S O M E
Hello ma'am. Can you send these photos as jpg or pdf ma'am?
In the last why we put n 0.60 i think why i not but 0.35
Very confused😵
Today is my exam at 1.30pm
mam can you send these notes???
Mam tell me about associative memories please upload this videos
When do you have exam and which clg
Please send the material type mam total ML
unit 5 vedios mam
mam can you please take whole number instead of decimal , just for calculation purpose
No
W6,w7,&w8 answer plss
Telling too fast so confusing
Watch 0.75x speed 😅
GAMIDI VENNELA ROSHINI 20BCE7376
1 second ago
can you please drop the formulas for w2 w3 w4 an in part 2 w6 w7 w8 please just the formulas
🥺
very complex :((
All this just for 10m
Very bad explanation part 3
Mam I am sharing u our 3rd chapter syllabus: please cover the leftover topics ... Pls mam
Convergence and local maxima
Representation power of feed forward networks
Hypothesis space sreach and inductive bias
Hidden layer representation
Generalization
Overfitting
Stopping criterion
And an example - face recognition