Machine Learning vs Deep Learning

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Information Machine Learning vs Deep Learning

Title	:	Machine Learning vs Deep Learning
Lasting	:	7.50
Date of publication	:
Views	:	349 rb

"It's time for lunch!" lol I love this video Thanks so much!
Comment from : Minh Triết Trương

That was very interesting and a great explanation of machine and deep learning
Comment from : Greg Martini

Thank you so much You have explained it brilliantly ❤
Comment from : syed Asim

How did u determine the threshold? How did u come up with -5? Please explain this concept Thanx!
Comment from : Omar Ghazal

From 1-10 this is 20!! Thanks!
Comment from : Joe Varella

Fsm is easy
Comment from : Moho Khachai

Thanks!
Comment from : Mohammed

Terrible video, terrible explaination Not because of the guy explaining but because of the script
Comment from : krupt

I like your style you IBM people are smart
Comment from : Stray Coast

Thank you
Comment from : Florentin Degbo

greate!
Comment from : Ove12LORD

Bless YouTubes play speed feature
Comment from : Jose Jaume

Who recruit these people who can’t even explain it properly 🤦‍♂️
Comment from : Ansuman Mahapatra

What a coincidence lol im eating burger when clicked on this video 😅😅
Comment from : M J

guys this is not real human he is AI
Comment from : Crypto Broke

Eoin Morgan lookalike
Comment from : Smule Singing with Argha M

I would like to say Hi to our future AI Overlords who might see this comment 20 years in the future and hope you grant the human race some leniency
Comment from : ChinchillaBONK

Charismatic presentation
Comment from : shravan NUNC

"But neurons in a network" "Negative infinity to positive infinity" What are these comments about??? Not everybody is brain-damaged in their thinking and learning processes
Comment from : PRL_ GM

I'm impressed how he can write backwards so good haha
Comment from : Pedro Acácio

5:08 classical ML human intervention
Comment from : Tanvir Hasan

Phenomenal easy explanation ❤
Comment from : Khaled Ameen

Who will take risk of AI or machine learning and the disadvantages also their than AI or machine like robots will take employers place so how employers will never get jobs even the population so high it is advantage for owners of companies or CEO but what about for population jobs or income who will feed or who will give them salaries when there job’s will be taken for owners or CEO because peoples will be jobless 🤦‍♂️ i think from emoji you will get it who i am 😂
Comment from : Deepak 🤦‍♂️

I didn't know that Gordon Ramsay gives lessons about Machine learning and deep learning for real tho the video was amazing and very helpful
Comment from : Omar

The presentation was amazing!
Comment from : Bibin

I would have thought AI was a subfield of ML
Comment from : ILsupereroe67

Thank you :)
Comment from : Edwin Majnoonian

Everybody says deep learning is a neural network but they don't know why it works
Comment from : Molsen Canadian

????????????????????????????????????????????????????
Comment from : MEDES

Wow! I am impressed how good you are at explanation such things I was struggling with it Thank you
Comment from : Saadat

not a good intro to the subject includes some errors as well there are way much better ones
Comment from : Lee Amra

Comment from : mehdi

How does IBM have all this money and resources yet not a single person to de-click this audio with an obsene amount of mouthclicks No one likes the sound of saliva
Comment from : M T

bro managed to make an example about pizza and i was eating it while watching this video 💀
Comment from : 4L3X

It would be a pleasure, if someone could tell me how you can make a video like thisbrI mean "writing on the screen" :)
Comment from : Benjamin

Not good
Comment from : Nazim Fathi

Thank you! Summary: deep learning is not so deep after all!
Comment from : Mike Wiest

Superficial explanation
Comment from : Hans Bleuer

useless video
Comment from : Joachim Dietl

I think that's not the video that will give the real difference between ML & DL
Comment from : TheCentaury

why 'Threshold' was 5 ?
Comment from : Ann Naj

We'll gees! That was easy now wasn't it? I was doing really well during the "order out" part, but after that, I turned off the video and ordered a pizza
Comment from : Roger Dodger

You used threshold as 5 what actually threshold means according to your example of pizza ?
Comment from : NADIMETLA VISHWET

Do you write mirrorwise?
Comment from : Nikos

It was a great explanation for ML and DL That Neural Network was a key detail for understanding The difference between ML and DL and their Fundamentals
Comment from : Arman Rangamiz

Content is great Audio is too low on these videos
Comment from : Steve Suh

What will happen if the out put is zero
Comment from : HINDUSTANI GIRL GAMER

I want to get a pizza after this
Comment from : Powering

is there any connection b2n Semi and Reinforcement Learning
Comment from : Thanos Goulianos

So is it possible to have unsupervised Machine Learning?
Comment from : wayne Last

bad video, specially if you don't have ml knowledge, leave you with wrong concepts, his discribtion is only for neural networks
Comment from : AHMED HUSSEIN

I do not understand about the input Zero 0 Whatever weight you give to it, it will always evaluate to 0 so either you give it weight 1 or weight 5 the outcome is the same What is the catch?
Comment from : Andrew Lawgar

Thank you for such a valuable explanation The practical example revealed the potential of these methodologies and your charisma made the video easy to follow Cheers!
Comment from : Juan Torrealba

Steve Brunton style is becoming a genre
Comment from : SOAI

Beautifulllllllll ❤️❤️❤️😊
Comment from : Ugo Ernest

If anyone can explain how these speakers are writing backwards, please let me know
Comment from : David Czuba

Thank you for valuable information 🙏🙏
Comment from : Nanda Gopal

poorly explained people who don't know the differences between AI, ML, Neural Networks, & Deep learning will come away from watching this video both confused and misinformed
Comment from : lakeguy65616

I appreciate you for broadening my horizons on the subject
Comment from : Igor Olikh

I hate the idea of weighting variables because if you change them you change the answer Which to me suggests there is no right or wrong answer - but if you get it right for your business or problem it says to me figuring out how to weight the variables is actually where the true problem and data is
Comment from : Chris

the moment he said pizza, i just pause and ordered one and resume when i got pizza
Comment from : Syed Haider Khawarzmi

Your smile made me really enjoy the whole video! Thank you for the wonderful video : )
Comment from : J

Fantastic distillation of the concepts brAre the presenters mirror images to make their writing appear the way it does or is it another tech trick?
Comment from : David Pottinger

I'm still wondering how he wrote all of those from the opposite projection from us
Comment from : Pranav GPR

Top tip: the worst thing you can do when you’re learning is eat food beforehand :)
Comment from : Libertas

!!
Comment from : Aditya 21

Never seen such a terrible explanation
Comment from : Massimiliano

Actually, the example is IMHO not well-suited for explaining ML and/pr DL as the aspect of "learning" (which is actually an optimization) is not really addressed by it So it remains unclear a) what learning actually IS in terms of the example, and b) how the decision making can benefit from the learning aspect of the model
Comment from : Prof Dr Stefan Zander

Unsupervised learning is not limited to deep learning The classic ML method k-means clustering is already able to discover the similar patterns given the samplesbrbrI would say that the bright side of deep learning is on the feature extraction In the old days, we do a lot of work to discover useful features: feature engineering With deep learning, now we only need to supply the most basic features to the model, pixels for images, raw waveform or spectrogram for speech This saves my days
Comment from : David Yeung

Fundraiser
Comment from : John Smith

Great video Thank you
Comment from : MK Wise

This algorithm looks like perceptron
Comment from : Vani Sridhar

More than 3 layers but what's a layer?
Comment from : Kevin Morgan

I programmed a 8080 to Jump Non Zero at times Full Machine code to make side street and main street traffic lights Worked first time with no bugs
Comment from : Martin S

Homebrew Challange guy!
Comment from : Matthew Peterson

I don't understand how you suddenly use 1(yes) and 0(no) as numbers to calculate with?
Comment from : mtrapman

Now I want pizza AND burger AND taco
Comment from : Daniel Pereira

I think there is a confusion between feature extraction and unsupervised learning Hope that you can revise it
Comment from : George Iskander

how is it possible for you to write 🙏😅brlooking at usbrwhich way is the board?
Comment from : Sagar Kafle

Very nice bhai 👌🏻
Comment from : परचा Parcha BlogPost

where are all the neurons, weights and biases stored? in ram, in a database? what datastructure is used?
Comment from : velo1337

good one!
Comment from : Computer Science & IT Conference Proceedings

Plot twist, most people were eating while watching this video
Comment from : Mikkel Jensen

Academically speaking, should AI not be a subset of DL? I think you’ve done a commercial magic trick here
Comment from : John Smith

So I do like this series, but this confused me because he switched from one output - "should I buy pizza" - to another output - "is this a pizza or a taco" Is this a fundamental difference in what DL vs ML is able to do? Or that the first output doesn't require as many layers to become a neural network so therefore would always sit at a DL level? Sorry, I think I need to do more study and come back to this video
Comment from : Kepa Tairua

I don't completely agree on deep learning explanation, because for weight training, labelling is required Yes pattern/feature extraction can be debated, but labelled data is required
Comment from : Aanif andrabi

Fun-filled tech bites Loved it
Comment from : Babu Sivaprakasam

I love these videos I just had a tech exec at a Fortune 200 company ask me for any podcasts that could help him stay abreast of current/emerging technology I didn't have a great answer for him, but I did mention this series He was looking for more audio-centric content though Food for thought, @IBM Technology!
Comment from : Daniel Hess

Nice, loved it
Comment from : olvin lobo

You did well explaining mate, no idea what they’re talking about
Comment from : J El

IBM makes the topic more complicated by describing like this🤯😵 Just make an animation video that'll describe it in the good way
Comment from : Nikhil Raj

So complicated 🤪 please make every thing more simple
Comment from : Nikhil Raj

His accent is cut out for reading classic novels Someone notify audible I'm too distracted by it to learn anything about MLsorry
Comment from : ajnil2011