Activation Functions | Deep Learning Tutorial 8 (Tensorflow Tutorial, Keras & Python)

Activation functions (step, sigmoid, tanh, relu, leaky relu ) are very important in building a non linear model for a given problem. In this video we will cover different activation functions that are used while building a neural network. We will discuss these functions with their pros and cons,
1) Step
2) Sigmoid
3) tanh
4) ReLU (rectified linear unit)
5) Leaky ReLU
We will also write python code to implement these functions and see how they behave for sample inputes.
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[@codebasics]

Do you want to learn technology from me? Check codebasics.io/ for my affordable video courses.

[@JunaidInHenan]

Hats off, I am a PhD student, and I worked on NLP, ML and text analytics, in the last semester of my PhD I am turning to deep learning for my post doc research, and I needed background information on deep learning. Also in my last project somehow I managed to apply deep learning simple classifier, but that instinct to theoretically and technically understand background of deep learning was missing. I read articles, videos etc. a lot but man your videos on deep learning concept is really fulfilling my instinct up till now. Hats off to you Bro. Thank you for your vision of education and these helpful tutorials.

[@arslanMCL]

Number of views is not doing justice to the quality of content that is created. Learning two weeks content in hardly 20 minutes. Thanks

[@codebasics]

I appreciate you leaving a comment of appreciation

[@karthikc8992]

sir what ah explanation , it seems so easy to learn deep learning,carry on your winning momentum , hope you become one of the great teachers in data science🔥🔥🔥🔥🔥🔥🔥🔥🔥

[@ansumansatpathy3923]

Very structured and organic build up of concepts, not throwing a bunch in a short timeframe down your throat praying you gobble it up. I appreciate your hard work behind the animations too.Keep it up!

[@abvijaykumar]

Very well articulated, I searched the whole web, nobody explained these concepts in such simple way, without any confusion!!! Thank you

[@shivam6565]

You are awesome. Complex topic explained so clearly that they just stick to brain. These lectures are of the highest quality. Thank you for sharing your knowledge and for free!

[@MrBasu-iq6md]

I do get valuable information from youtube now and then. However, I did not expect deep learning tutorials to be explained in such simplicity yet highly informative as well. Machine Learning and Deep Learning videos on this channel are highly recommended.
Thank you for such contents.

[@SKumar-Munna]

I am watching your video since beginning. All is amazing Sirji.

[@sayochikun3288]

wow this channel has a lot of crucial content. relu activation decreased my loss value from 0.04 to 0.003 even with half of training data!

[@nikolaynedelchev1644]

Thank you very much! Such a great explanation. Thank you for explaining the pitfalls in the activation functions - it is for the first time I hear them.

[@codebasics]

😊👍

[@ChristopherUOnova]

Thank you once again for making Machine Learning simple...God bless.

[@mallikamehta3928]

this was extremely important, cleared my all doubts and now i think i m able to solve problems myself thank you so much, god bless you

[@mytechwork6351]

sir, you give a good concept of deep learning. Sir i am beginner and one my friend refer your deep learning lectures when i started your lectures i learn so much from it. Sir keep it up for future, thank you sir again..

[@shreyakapadia3735]

I really loved the easy explanation given by your sir. I wish I'd found this series earlier, but will watch the series from now on. Thank you for your efforts.

[@codebasics]

All the best Shreya

[@jas13]

Your videos are excellent. Your words and diagrams really help clarify the process. I have recommended your videos to fellow colleagues. Bravo 👍

[@wishIKnewHowToLove]

The best UA-cam teacher!

[@umarnadaf7170]

i am getting more attracted to words deep learning by ur explaination wt a explaination great sir hatsoff

[@juanpablobazan5716]

Thank you so much for all the tutorials! You are the Man!!

[@user-yy3ts5pf8k]

Nice series of tutorials. Super easy and time-efficient explanations.

[@gourabkundu7476]

Best Video on UA-cam on this topic

[@milchada]

Thank you! Your tutorials are helping me get started with CNNs for my research!

[@codebasics]

😊👍

[@quaternion-pi]

Excellent series, clearly explained Thanks.

[@muhammadrizwan727]

Hi Sir, Amazing, I watched many videos in UA-cam regarding Deep Learning or Data science, But i failed to find this type of help, lectures, mentoring. Hats off. A bundle of thanks and prayers for you from Rizwan (Pakistan). Keep it up.

[@codebasics]

Thanks Rizwan for your kind words and glad these videos are helping you 😀

[@nikitasharma2757]

Great explanation sir, I refer to all your videos for explanations.

[@work-dw2hl]

Awesome explanation plz continue this series

[@mustafizurrahman5699]

BOSS BOSS, one of the best pedagogue

[@sabarezaeekhavas7227]

I want you know that you are wonderful. I really enjoy watching your tutorials 💟

[@sidduhedaginal]

Your explanations are always classic and very detailed even undergraduate student can start learning DL during his course.
Keep it up sir....keep good health.

[@codebasics]

👍😊

[@komalteke1248]

Thank you so much .... The way you are teaching big big concepts with so much of easy understanding... it's really very very good... keep going....

[@codebasics]

I am happy this was helpful to you.

[@hannibalbra1216]

Brother u are a savior god bless you

[@Breaking_Bold]

GREAT explanation ..this video and all the others in the playlist.

[@arashnozarinejad3576]

incredibly informative video sir, thank you

[@dudefromsa]

This is brilliant indeed Dhaval

[@dhruvkantsharma2955]

Thank you for such an amazing tutorial!

[@codebasics]

Glad it was helpful!

[@fahadreda3060]

Thanks for the video .. wish you all the best

[@its-me-Padma]

big fan of this tutorials

[@Xiaoxiaoxiaomao]

love your tutorials ❤❤❤

[@DukeOfCurling]

Great explanation!

[@mithlesh0singh]

Just love the way you explain.

[@codebasics]

thanks mithlesh

[@user-cz6ht4ot7o]

SIR HOW YOUR CONCEPT IS TOO CLEAR ON ANY TOPIC? AWESOME Sir🙏🙏

[@_AkankshaPatil]

Thanks a lot, sir for such an amazing tutorial

[@ishapandey48]

Understood well...thanks sir!!

[@goodwork9577]

There is no better explanation i've come across when it comes to Data science/ Machine Learning/Deep Learning, it's a shame that big e-learning companies like edureka are just copying content as mentioned by dhaval sir in one of his recent videos.

[@petcristi]

Great work!

[@convergence549]

Thank you brother you explained it very well

[@priyabratapanda1216]

Really very intuitive indeed!🙏🙏🙏🙏

[@codebasics]

I am happy this was helpful to you.

[@chipsafan1]

Great video! Thank you

[@artipunit]

Best explanation ever. Will share for sure

[@codebasics]

Glad it was helpful!

[@amitjaiswal781]

Very nice and easy explanation sir.

[@shamsunder5353]

Simply fantastic

[@unnamednolast7701]

thank you so much i have learned so much

[@mimohraj1045]

maths parts must be known to the learner because to understand the problem statments , and your lecture help me a lot thanks ,,,,,,

[@ankkush4898]

Very useful....made it very easy...thank you

[@codebasics]

Glad it helped

[@mechanicalbaba2484]

Thanks you sir, now I am finding deep learning kinda easy

[@codebasics]

Glad to hear that

[@shiv19811]

very nice videos....good work

[@deepthikiran8345]

amazing tutorial.....right to the point...thanks :)

[@codebasics]

Glad you liked it!

[@beautyIsinEverything753]

nice and clear explanations thanks

[@sanobernishat223]

Amazing teacher

[@245uday]

Well explained sir...waiting for next video

[@codebasics]

😊👍

[@61_shivangbhardwaj46]

Very helpful video sir☺

[@SwarnaliMollickA]

Amazing!

[@sanooosai]

thank you great work

[@bangarrajumuppidu8354]

super explanation sir!!

[@codebasics]

Glad you liked it

[@utkarshpandya3155]

very nice concept

[@amandeepsaha]

Sir u r amazing

[@kashishvarshney2225]

really amazing

[@ranakarmakar5141]

thank you for this playlist

[@amirhanna6270]

Excellent

[@mayankvekariya8199]

I like your all videos

[@codebasics]

And I like your comment Mayank :)

[@dec13666]

Nice explanation 😎👍

[@codebasics]

Glad it was helpful!

[@shahajadealam9684]

superb video sir 💕💕💕💕💕👍

[@codebasics]

Glad it was helpful!

[@darktarifa7200]

Thanks for your explaniation

[@codebasics]

Glad it was helpful!

[@manishdas6525]

dhasu 🔥

[@NazanTem]

Thank you!

[@shikhasen3981]

Hi sir ,
I want to be as great as you are at dat science .
just a question , is neutral network good for classification or can we forecast the regression as well ?

[@MAK_3583]

good tutorial

[@jongcheulkim7284]

thank you so much.

[@mohitb5230]

well done

[@vijayalaxmiyalavigi6232]

Sir, thank you very much.

[@codebasics]

Glad it was helpful!

[@shubhangiagrawal336]

useful video

[@sayantanmitra7897]

This is really helpful. Could you please provide the slides?

[@ayushi6424]

Sir please include softmax activation fuction also..can u give me brief of it...because i m using it in my project

[@akhiljohnson6019]

Sir, what is the significance of traditional ML algorithms (eg: Linear Regression, Random Forest etc) if deep learning is becoming so popular?

[@karthikc8992]

Use of ml algorithms train data with good accuracy if our data is small
.
When we have tons of Data , using deep learning can fix with good accuracy
If the data is small deep learning cannot fix good accuracy

[@akhiljohnson6019]

@@karthikc8992 Ohh
Thanks for the info ☺️

[@priyabratapanda1216]

Also it's very difficult to handle a deeplearning model than a machine learning model.
Also you might have noticed deeplearning models aren't quite responsive as compared to ML model as it requires a lot of time for training.
Another thing you only go for deeplearning when you have tons of data's otherwise you'll end up overfitting your model.

[@Bulbulgoyal672]

thanku sir

[@tewodrosgebre204]

thank you

[@shafagh_projects]

congrats for your lovely tutorial. is C++ being used for deep learning? or Python is the top list of industries for AI transformation.

[@codebasics]

Python rules the ML world. People use C++ but rarely

[@neuraspike]

Nice tutorial. How do you make the drawings used in your presentation?

[@codebasics]

Power point. I make them on my own from scratch in power point

[@saurabhbarasiya4721]

Thanks

[@kirankumarpaturu2239]

sir thank u so much

[@codebasics]

Most welcome kiran.

[@shivasiddharthnarayanan]

Thanks for the great tutorial....
Not sure if this query is right. Sir, while explaining ReLU the mark of 1 at y-axis is not correct, I guess......Please correct me if I am wrong....:-)

[@rathnakumarv3956]

Sir, what about softmax activation function, only for multiple classification? any other activation function for time series analysis?

[@anirudhsrivastava3530]

@2:52 Sir, can you explain in detail the non-linearity part of activation function

[@md.tahmidulislam5965]

Can you please tell something about Asymmetric Activation Function in Neural Network ?

[@debatradas9268]

thanks

[@jaysoni7812]

can you please make a separate video on vanishing gradient.

[@codebasics]

sure will do

[@sudhakarm4573]

Dear sir.. request to make videos on Boltzmann machines

[@rizalmuhammed7816]

Can you also upload the presentation slide in the github link for quick occasional revision. Thank You

[@grandhimanikanta7522]

At what value of "tanh" neuron will activate/fire the output to the next neuron?

[@NnGgnT]

Hi man, I think at 10:11 the ReLu function is : ReLU(z) = max(0,z) insted of max(0,x)