Sir we are finding the difficult to crack the job in data science placement so please make a dedicated 100 days series of placement tricks & tips, Requested everyone to upvote it , so that sir notice it
I was looking for perfect GD in short video, and here it is, literally the perfect one so far,, great job and effort I must say. keep making short videos like these.
Good Content, Great Explanation and an exceptionally gifted teacher. Learning is truly made enjoyable by your videos. Thank you for your hard work and clear teaching Nitish Sir.
16:24 but i feel that SGD will take lesser time , because if we apply Batcg GD , it will update weights using whole data set , say its a data set which has 2 million entries , it will take more time , vese SGD will also take good amout of time in this case , i think we cant say which one will take more time in such cases , time taken depends on a lot of factors , so we cant clearly say that BGD will take lesser time .
Awesome man ... big thanks.. I was very confused about batch_size .. After watching this video i found to know that there is relationship between batch size and gradient decent ❤️❤️ Now deep learning is getting interesting to me
Hey Nitish, can you please tell me which tracking/writing pad did you use in your Machine Learning playlist videos. In the current ones your using a Samsung tab. What about the previous videos? Also could you please tell me the size of it too.
sir ,can you explain what is the difference between GD and Backprop Algorithm , though both are calculating derivatives (chain rule in Neural nets) and then updating weights. I know its kinda silly question to ask
Hi sir i think u have mixed sorcastic and batch when u were explaining the 2 graphs u plotted so batch will give u not stable curve but sorcastic will give u more stable or smooth graphs Bcs more points u have smoother the graph will be less points u have not smooth the graph will be but in batch u have less no of times u have updated the w and b so less points So i dint follow ur logic Also sir even stocastic gradient descent uses for product to calculate y pred so both places ur using dot product so please can you explain me why are you saying that dot product is replacing the loop on batch bcs ur using dot in both the algorithm
Sir we are finding the difficult to crack the job in data science placement so please make a dedicated 100 days series of placement tricks & tips, Requested everyone to upvote it , so that sir notice it
watch sir website for this
@@Harshupadhyay-u9d please provide name of course and is it paid or not ?
@@janardhan1853 paid
I was looking for perfect GD in short video, and here it is, literally the perfect one so far,, great job and effort I must say. keep making short videos like these.
You are an excellent teacher; you explain everything in detail so that concepts become clear. Thank you so much for your efforts.
You are an excellent teacher; you explain everything in detail so that concepts become clear. Thank you so much for your efforts. You are truly a gem.
Sir videos kafi acche hai seekhne ko bhi bht kuch milta hai bs sir time continuity banaye rkhie sir, kafi wait krna pad jata hai apke videos ke liye
i thankyou from bottom of my heart i am a dataengineer looking for career transition and u made concepts very clear.Thankyou!!!!!!
What a fantastic teaching method; great job.
this video contains good content so pls change the thumbnail and put it attractivly like ur photo with background this topics
Good Content, Great Explanation and an exceptionally gifted teacher. Learning is truly made enjoyable by your videos. Thank you for your hard work and clear teaching Nitish Sir.
Wow!!clear explanation i never got from anywhere
16:24 but i feel that SGD will take lesser time , because if we apply Batcg GD , it will update weights using whole data set , say its a data set which has 2 million entries , it will take more time , vese SGD will also take good amout of time in this case , i think we cant say which one will take more time in such cases , time taken depends on a lot of factors , so we cant clearly say that BGD will take lesser time .
Best explanation on gradient descent
Mind-blowing class
Thanks for the wonderful explanation!
Thank You Very Much Sir.
Awesome man ... big thanks.. I was very confused about batch_size .. After watching this video i found to know that there is relationship between batch size and gradient decent ❤️❤️ Now deep learning is getting interesting to me
Bahut aala... 😊
Easy explanation , Thank You
Always like your video before watching it.❤
what is the use of shuffling the data set in SGD , vese bhi randomly samples choose ho rhe hai , in Mini Batch it is fine
Sir please provide short notes for this which will help full for us
How to apply mini batch gradient descent. Please show the implementation
intuitive
19:15 i feel like results will be different in case of bigger data sets
So good
Thank you so much sir
sir,please suggest me some projects od deep learning
for college resume
Sir apne Lectures ko compile kr k book bna do...
Need to buy
Awesome
Bole tho jhakkas Bhai!!..
Nice video sir
can a get teh dataset please
Hey Nitish, can you please tell me which tracking/writing pad did you use in your Machine Learning playlist videos.
In the current ones your using a Samsung tab. What about the previous videos?
Also could you please tell me the size of it too.
Wacom 6 inch * 8 inch
@@campusx-official thanks so much
Bhaiya ML projects ke playlist me kuch add Karo na please!!!
sir ,can you explain what is the difference between GD and Backprop Algorithm , though both are calculating derivatives (chain rule in Neural nets) and then updating weights. I know its kinda silly question to ask
In back propagation to calculate the loss gradient descent is used.
backpropagation is a type of training method in which gradient descent is used.
Best Explanation
u r great as always nitish!!
bhai tune to youtube chod diya tha na .. can anyone clear me on this what actually that video was about?
April fool
😂🤣🤣
how can u shre one note ,note with us
great Video
fantastic....
best explaination
Nice 1 bhaiyya
Outstanding
Hi sir i think u have mixed sorcastic and batch when u were explaining the 2 graphs u plotted so batch will give u not stable curve but sorcastic will give u more stable or smooth graphs
Bcs more points u have smoother the graph will be less points u have not smooth the graph will be but in batch u have less no of times u have updated the w and b so less points
So i dint follow ur logic
Also sir even stocastic gradient descent uses for product to calculate y pred so both places ur using dot product so please can you explain me why are you saying that dot product is replacing the loop on batch bcs ur using dot in both the algorithm
he didn't. Google this topic on geeksforgeeks "ML | Stochastic Gradient Descent (SGD)"
Thanks 🎉
8:34 50 points ka loss aik sath calculate ho kae avg ho ga? otherwise tou loss buhat bara ae ga i guess.
GREAT CONTENT
Thank you Man
Thanks sir
sir ek Python interview ka series bna dijiya sir if it is possible.
25:20 😂🤣🤣🤣
❤
Revising my concepts.
August 11, 2023😅
best
Very best 👌 sir
❤❤❤
Please covet Adam and other optimization techniques also weight untilaization process ,leqening rate decay
Sir i wanna recommend your videos to my south Indian and international friends.. plz make some videos in only English too..thanks:)
na bhai hindi me hi bana ne do aap krish sir ka video dekho ruclips.net/user/krishnaik06
❤❤👏👏👏
great explanation sir
image processing
kindly sir
Ambani mere 🦜🦜
finished watching
who r u man🤣
kindly sir aghar ap k sare one note k notes mel jae
🤍
please add English Subtitles to your Videos
Thanks Sir