Domain and Web Services
this is good
The best explanation of convolution in few minutes.🙏this is good
I've seen this guy somewhere, Coursera maybe
Please provide a budget Chromebook with a Google TPU for machine learning
If you don't like Python for some reason, you can write basically the same code in C#. See https://habr.com/post/453232/ for an example
One thing that always confused me the initialization of those random factors like how many neurons should I put what activation functions should I keep for certain layer and most importantly what would be the architecture of my whole NN for performing a certain task can anyone help and throw some knowledge on these ?
Can you please share that code with me which you used in jupyter notebook ? I would be very happy for that.
Wow .. this was an awesome presentation, I'll focus on the first speaker since I was somewhat familiar with the subject (I also liked the second one).
He explained all of the key concepts as clearly as I have seen – and I have looked at a LOT of videos, this is a master class in how to do it. I hope he presents on many more related topics. Definitely worth watching.
Thank you so much!
I've been waiting and waiting thinking the only way to properly learn machine learning is through university courses. I've been wrong. I appreciate the work you guys are doing to motivate the next generation of programmers to understand that machine learning is something anyone can understand and use as long as you've put the effort in. Thanks guys 🙂
Just FYI…Henri Poincaré, French mathematician: https://en.wikipedia.org/wiki/Henri_PoincaréHow to pronounce "Poincaré": https://www.youtube.com/watch?v=zYF7UFY40iE
I've seen you on CourseEra!!BTW best explanation ever!
I love the idea, but installation using Anaconda with Windows makes Spyder and/or Anaconda prompt unresponsive. This problem also occurs when using Keras because TensorFlow is the back-end. I think I've got a working set up now but this was after 2 un-install and re-install attempts.
Stuff like this makes me so happy I'm a cs major
Are the convolution functions created by human or self-generated based on usefulness?
Laurence Moroney is a golden god xD Concise and well presented.Thanks for your inputs, cleared up all my foggy areas on this.
Nice explanation about why we use CNN to get features applying different filters rather than just flatten the image pixels as input,but why she is standing back there all the time
From zero to hero.. thnx
In case anyone is interested, this is the link to the notebook used during the presentation: https://github.com/lmoroney/io19/blob/master/Zero%20to%20Hero/Rock-Paper-Scissors.ipynb
Awesome presentation! Thanks Google❤️
Very good presentation. Concise and to the point.
Great talk! Helped to clear gaps in the understanding of conv nets
This is basiclly comunication theory haha
So they put in a bunch of answers, the machine leaning catalogs those answers with similar attributes, and creates rules which constitute the best answer concerning the outcome of similar answers against each other.
Thank you for the useful video. I am curious about deep learning and your explanations showed me a lot of useful insights.
Guys presentation – logical, step-by-step in easy language. Girls presentation – filled with special slang, with logical jumps, horrible.
I remember when Laurence taught in Coursera "Tensorflow in practice" course how to recognize that same rock, paper and scissors images, and in the way that he explained it was pretty easy to implement. Excellent teacher!
Nice explanations and tools. I think mainly why I am struggling to make use of machine learning is because I am attempting to implement it from scratch.
Normal people will have access to AI. Scary times.
(Aside from the talk being great) The presentation screen is awesomely beautiful!! Imagine seeing this for the first time, even just from year 2000.
I’ve been looking into ML & Supervised Learning. Looking to make a connection with a PU professor
Super presentation! Nice explanation on concepts in Machine Learning using TensorFlow, 'Convolutional layer,' and 'Pooling'.
This is the best tutorial/introduction that I have ever watched
And somebody please give this man a hand of applause!
The photoshopped hands are extremely off putting but good video otherwise 😛
This man is saviour 👍🙏
i wish i was smart enough to learn this
Can someone please kindly post the links to the code and datasets? Thank you!
meaning of convolution lol
Can i convert such a model to actual c code?
I want to learn ML.please anyone suggest me which software is best.
Amazing. One day.
Can someone send the link of code of rock paper scissors please
Now only to check wtf are gpu, cpu and leart that python.
8:58 , crystal-clear explanation of "Neural Network".
Imagine if you were to feed millions of people’s medical records, all known medical research, etc. into one of these models.
Finally, I got this shit. I have been watching various speeches and talks for the past two years and every time I thought I got it, I didn't. Of course, until I stumbled upon this video. Now I know the concept enough that I can explain it to both technical and none technical people. Thanks for the wonderful video.
plz keep publish like these videos that help AI coders to proceed the trip of learning and applying
Excellent overall. This will be obnoxiously nitpicky, but Poincaré is pronounced pwan-car-ay.
I need this presentation
Soon programmers will disappear when AI writes itself.
But that requires some good background in calculus? Tell me if I'm wrong. That's the reason I haven't started yet.
Thankfully some love for POINCARE!!! (instead of that scumbag scammer "einstein")
Which one is the course on Coursera? I might do it as soon as I finished my current course I'm doing. Thanks for the video.
its simply awesome, i been using jupyter note book, and it has cleared my many queries running in my head, and lot more still remaining,. Good work.
Can I use tensorflow in .NET environment? Nice tutorial
Is it advisable to write your code using such shortened, simpler libraries specially in areas of higher studies like PhD ?
You don't need tensor flow you can use Excel and Java . And it's incorrect to say that it's hard to code it in java. The important part is the training data and lots of it. This is just a Google ad but at least the audio is good.
Hi This man is amazing , I would like to say he just remind me with old days in faculty of science , 1992:as we in normal programming we have function f passing it a value x ,then waiting for the result Yi.e Y =f(X)However , in ML we have both values of X & Y and ask the machine to suggest the most accurate function f(X) . Thank you , I knew you and checked out your courses at coursera .
I love the way they talk. Excellent, I learned exactly what I was looking for))
Am i the only one to notice that missing parenthesis on line 2 on the time 9:22 🤔🤔
Whats the purpose of multiple convolutions? So you do the convolution to highlight features and simplify+shrink the input data, but what are the following convolutions do? Are they applied to the already modified data, or to the unaltered clean one?
Same location, different purpose 😉https://www.youtube.com/watch?v=wYrmwUy6kz8
Thanks a lot for your helpful presentation
So simply explained, this is amazing, thank you
I thought she was just an assistant.
No one ever explain ML this way to me . I have a new prospective of looking at it.
I have to admit that this lecture is mind-blowing!
awsome tutorial ever sir. I like the way you explain things up to the novice level. Hope you will help me solve the following error I am getting when I try to run it on jupyter notebook.
import SimpleITK as sitk
import numpy as np
This funciton reads a '.mhd' file using SimpleITK and return the image array, origin and spacing of the image.
# Reads the image using SimpleITK
itkimage = sitk.ReadImage('C:UserstekSampleNodule')
# Convert the image to a numpy array first and then shuffle the dimensions to get axis in the order z,y,x
ct_scan = sitk.GetArrayFromImage(itkimage)
# Read the origin of the ct_scan, will be used to convert the coordinates from world to voxel and vice versa.
origin = np.array(list(reversed(itkimage.GetOrigin())))
# Read the spacing along each dimension
spacing = np.array(list(reversed(itkimage.GetSpacing())))
return ct_scan, origin, spacing
when I run it is saying, File "<ipython-input-3-aceebef52c30>", line 7
SyntaxError: invalid syntax
Machine Learning Demystified 😀
Salute to you Laurence what a great explanation!!
11:55 what happens at the borders of the image?e.g. you wanna calculate the "next pixel value" (pixel value for the convoluted layer) and you take the pixel [0;0] — if you now want to apply the filter to the surrounding pixels you'll read from the image pixel -1 to 1 in x and y direction. Is Tensorflow repeating the borders? Does it fill with zeros or ones? what is happening here and how can you specify it?
I got lost when he talked about the functions mapping pixels to a prediction. what do the functions do?
Very helpful explanation by Laurence! Hope to find more of his videos.
Crystal clear explanation 👌👌
is this the crispiest hd quality video on youtube? Excellent content too
very informative, thank you.
Thank you! Always eager to learn.
14:20 why isn’t 226 taken if that is the highest number out of all 4
Unrelated. But I was in the hospital as my baby daughter was being born as this event was occurring 🙂
Very enlightening talk.
How long an ML noob like me who is rather experienced Android Kotlin dev would take to create a similar image recognizer app?
I'm not understanding why the 150×150 image be omes 148×148.
God ! That screen ❤️.
amazing, this is pure genius, if you want to learn more, look for tensor flow coarse on coursera
Why 512 in the 2nd line of the model code? How do I decide on this number? How to decide on loss and optimizer?
Imagine using this amphitheater for a rock concert!anyhow Im now switching from pytorch to tensorflow
I need the right code
This was just amazing
Really enjoyed the cat speech !
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