Brandon Rohrer
Find the rest of the How Neural Networks Work video series in this free online course:
https://end-to-end-machine-learning.teachable.com/p/how-deep-neural-networks-work
An explanation for deep neural networks with no fancy math, no computer jargon. For slides, related posts and other videos, check out the blog post: http://brohrer.github.io/deep_learning_demystified.html
Follow me for announcements: https://twitter.com/_brohrer_
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Wonder what happens if that cooking robot gets hold of HowToBasic videos
…опять один внешний пиздёж… около этой проблемы…, скажи суть…!!!, не можешь…, скорее всего не знаешь…!!!!
Hi Brandon, just watched both your talks on deep learning. I found them to be the clearest presentation so far on the subject. Thanks. Why do image recognition nets use such low res photos to train with. I mean some of the feature like blood vessels or hairs on the skin would be useful for classification. Is this a hardware issue or do higher res pics just confuse the nets.
Audio volume is rising and falling.
Great talk, you did an awesome job explaining. I'm interested in seeing future applications; is there any code available online?
Thanks Brandon Rohrer for detailed explanation of concepts. Initially I saw your video on Linear Regression which is part of How Data Science Works. Later I had to search a lot to find your channel. Once again thanks for such videos and distributing your knowledge on Data Science.
Amazing, way to go Brandon it was surprisingly very easy to understand, great presentation
Very informative!
great lecture, thumbs up. One suggestion, where a lavalier mic so we can here you when walking away from podium.
wow that was cool ,
thanks for create this
Are not numbers just names we give to quantities or values? And are not names just variables with multiple possible values based on context? Maybe it would be better to talk about value vs variable instead of name verses number.
the best explanation i've ever seen.
I watched this hoping I'll learn something new about Deep Learning but all he talked about was Multi-Layer Perceptron. I haven't had the chance to study Deep Learning yet but I'm pretty sure it's not just a new name to MLP!
is there software for image recognition in deep learning and exit xml wait file
thanks-it makes sense!
i thaught i was watching a video about machine learning but now it turned out to be about airplanes… #thanksunited
hi Mr Brandon Rohrer i need to use Deep Learning in character recognition could you help me please thank you
"You can substitute magic for deep learning and it fits perfectly"
Magic Demystified
The voice quality of all of the videos are pretty bad
thank you very much
this audio is PAINFUL to listen too. my computer and speakers are at 100%, can barely hear speaker, then at times volume spikes.
sound engineer should be ashamed.
but what is gradient and delta @14:38
Santos Dumont Air Plane. 😀
the am/pm example is not great, @10:50, you kind of lost me with this example. I was completetly unable to understand what comes after… Really, choose your examples wisely.
is that moning at 1:32
GREAT
Excelente.
Love it, the best explanation of the Deep learning that I have ever seen, it connects the biomedical mechanism, and AI together, brilliant!
If Estopa, an spanish band, is similar to Police or Bee Gees, something is not working well in Spotify; or Alaska y Dinarama, I love them, but they are quite different to Daft Punk.
Thanks for the videos. You explain really well.
I've watched a dozen of these and I got to say that this was the best. It explained the basic concept added with some computational logic without going to deep in the math right away, this seems to be a tough combination to find. Many thanks!
how is nobody bothered that he's showing the slideshow the wrong way?
I got bored… Thoroughly bored….wanted to run away….but was forcing myself every moment to.complete the video..I slept in the end…
OrchOr. Brains are quantum
L01568916O
Lvl up Intelligence 1,000
Hey.. Congrats for your video!
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It is interesting, but the sound is off. The speaker should have carried the mic on him.