This is such a great explanation. So much important information is packed into this one video. Thank you very much for saving my time! keep up the great work. The programming community needs more people like you
Finally someone who understands it. I can`t believe how people lack ground knowledge in plotting functions, but are already studying Maschine Learning. Thank you very much.
Thank you so much, this really helped me grasp the concept. I always wondered how big inputs (or many inputs) result in 0-1 ranges when leaving the node, since they are all added and multiplied beforehand. I knew the activation function takes care of it, but had no idea how exactly
This was great. Had heaps of trouble finding something that explains why the function is written the way it is. Thanks. Any ideas why we specifically use Euler's Constant vs any other. Or is that just because it's commonly utilised as a "Natural" exponential function?
This video was an incredible help, ty for making it. Does anyone know why there's a limit for x=0? I thought limits were only for when x neared impossible values, but x=0 doesn't seem to break anything? My knowledge of calculus is still pretty low. Thanks.
We take limit at x=0 just to find the threshhold value of sigmoid function so that we can draw the border point or threshhold point on the basis of that value we can predict either our independent variabe lies in 1 category(in this case Cat) or in second category(Dog)). hope you understand.
Unfortunately, mathematicians cannot explain mathematics to non-mathematicians 😅. If i would explain the Sigmoid function clearly, I would start with the problem itself and what should be solved, before I start with any numbers and formulas.
so in other words, the sigmoid function should be used only WHILE training, then testing should just use a comparison operator to see if the value is more or less than 0.5?
It's so funny when you realize that videos with superficial concepts of AI have a lot of views, and videos with specifical topics just have a few views
![Logistic Regression [Simply explained]](http://i.ytimg.com/vi/C5268D9t9Ak/mqdefault.jpg)
I'm shocked to see that this channel is so small. Please keep uploading, you're a goldmine.
Truly CLEARLY explained! Good job. I look forward to seeing the rest of the series.
This is the clearest explaination ever made. The world needs more people like you my friend. Thank you so much, you are a game changer.
I decided to learn a little bit about the sigmoid so I could understand neural nets slightly better, and I'm glad I did. Very good video.
This is such a great explanation. So much important information is packed into this one video. Thank you very much for saving my time! keep up the great work. The programming community needs more people like you
Finally someone who understands it. I can`t believe how people lack ground knowledge in plotting functions, but are already studying Maschine Learning. Thank you very much.
THIS IS THE MOST AMAZING VIDEO ABOUT THE SIGMOID. It really helped me understanding better machine learning @16
Thanks for the video! Very easy and clear to understand the Sigmoid function.
Amazing explanation. Looks like I will never forget this concept as it was explained so well.
Best way of explaining it in my eyes. Cheers!
Ah.. because I didn't learn math properly, I couldn't understand why is this working as binary activation. Thank you for explaining.
woow, I didn't think I would get the idea in a youtube video
thanks!!
Thank you so much, this really helped me grasp the concept. I always wondered how big inputs (or many inputs) result in 0-1 ranges when leaving the node, since they are all added and multiplied beforehand. I knew the activation function takes care of it, but had no idea how exactly
Epic pfp
Thanks for a clear and to the point explanation...
thanks, your video is easy to understand, hope you keeping working on more things like this.
This is amazing! Perfectly explained!
You should create more videos. Beautifully explained.
clear as day. Thank you for the amazing explanation
This is fantastically visualized and explained! :D
EXCELLENT explanation. Thank you!
Really clear and straightforward explanation, thanks a lot!
Keep it up guys we really appreciate your effort
The best explanation ever
Best video on the topic. Thanks
Why would anyone dislike? Beautiful presentation and explanation.
Awesome! Clearly and concisely explained! 👍🏼👍🏼
Great explanation. Thank you!
This video is amazing, great job!
Exelente explicación! ¡felicitaciones eres un gran educador!!!!!!
Good job I hope to continue
Thank you so much for this detailed and informative video!!
Simply yet effectively explained. Please consider making more videos & continue. I visited you channel, that was your great initiative.
Very helpful!! Keep up the good work. Thanks
Thank you very much. Clear explanations. Cheers!
This video is just perfect.
Thanks a lot buddy.
Thanks for watching :)
job well done ...thank u for spot on explanation
thanks for the detailed explanation!
Thank you so much now the intution for the formula for logistic regression for classification problems became much more clear 😀
Great explanation, thanks a lot!
Thanks for watching :)
amazing channel, I hope that you can upload more videos
Wow.. Amazing presentation.
thank you, clear, concise, and I liked the graphics
Awesome explanation, thank you 👍
Wow nice explained
very nice explanation!
awesome video! thanks so much for this
What a wonderful video!
This was great. Had heaps of trouble finding something that explains why the function is written the way it is. Thanks.
Any ideas why we specifically use Euler's Constant vs any other. Or is that just because it's commonly utilised as a "Natural" exponential function?
yes, exponential uses e by default.
Waiting for new videos bro. Excellent explanation 😁🤠
Best visual explanation!
Good explanation!
Wow, thus a very great explanation
The inverse of e^x is not e^-x. That would be the reciprocal. The inverse is ln(x).
Both notations are same right? 🤔
Well it is the multiplicative inverse
that was concise and simple. thank you very much!
loved the explanation mate!
This is a master piece
amazing explanation
Very cool, thank you.
This video was an incredible help, ty for making it.
Does anyone know why there's a limit for x=0? I thought limits were only for when x neared impossible values, but x=0 doesn't seem to break anything?
My knowledge of calculus is still pretty low. Thanks.
We take limit at x=0 just to find the threshhold value of sigmoid function so that we can draw the border point or threshhold point on the basis of that value we can predict either our independent variabe lies in 1 category(in this case Cat) or in second category(Dog)).
hope you understand.
Unfortunately, mathematicians cannot explain mathematics to non-mathematicians 😅. If i would explain the Sigmoid function clearly, I would start with the problem itself and what should be solved, before I start with any numbers and formulas.
Also important to put in that the Sigmoid function is a special case of the Logistic Function with the parameters L=1,k=1 and x0=0.
very good explanation
wow this is perfect man
Excellent
so in other words, the sigmoid function should be used only WHILE training, then testing should just use a comparison operator to see if the value is more or less than 0.5?
Great explanation. Thanks
Thank you!
Even after watching it carefully I did not understand it properly can someone tell me the pre-requisites to understand this?
zero, except the last part where he told about classification problem. There is nothing to learn, he told everything in video.
@@lordblanck7923 okay
@@arfatahmedansari8916 yes, you'll need to learn basis - intermediate calculus for this
@@lordblanck7923 that's an absolute lie
he has a nice voice !
very enlightening, thanks for it
So useful
Thank you for the clear explanation.
Thank you. Good Explanation
It's so funny when you realize that videos with superficial concepts of AI have a lot of views, and videos with specifical topics just have a few views
understood. tks
My pleasure 😇
hmm
inverse of y=e^x is y=ln(x), yea?
you were just putting a negative over the x not the inverse.
But super nice video of sigmoid func!
I think he meant reciprocal.
This was great. One doubt. How does (lim x -> neg INFINITY) makes (e power minus x) -> INFINITY
Clearly explained indeed.
very useful thank you!
Clear explanation
thank you, great explanation.
Yes!!!!!!! this is us humans making other lifes easier!!!
well explained👏
when i codded a sigmoid function and inputted -10 the value was greater that 1
Then your code is wrong
Very good
👍👍👍
wow, amazing !!
this is great 🔥
ahhh dogs and cats. ai youve struck again
Thank you 😊
Follow me on Medium: dr-younes-henni.medium.com/
Thank You
Thanks!
diminishing marginal returns indeed - lets change a few benchmarks 2023!!
👏
Excellent Body :)
bros negative pronounce seems to be raciest lmao😆😆😆😆😆
😂bruh u mentioned that, and now i cannot ignore it
Very well explained, thank you!
Excellent
Thank you