A note on the Federated Learning example in the Colab tutorial (which is also pointed out on the OpenMinded tutorial) - this is meant to show how the learning process works when you're pulling from separate datasets, but this process actually doesn't ensure privacy! You can call model.get() to learn about how to predict well on Alice's data without having seen it, which can help you learn more about the dataset itself, even potentially replicating it perfectly. A way to avoid this is to average Bob and Alice's model updates before sending them to the global model as we talked about in the video! Thanks to u//raj111sam for pointing this out on the r/artificial subreddit.
Great video I’m a Technical Pm and been heavy in Data and Analytics. What are your thoughts on the MIT Business Analytics 6 weeks program? What do you recommend?
4 года назад+5
Hey Jordan :) I am a postdoc researcher based in Japan, but originally from Brazil. I have started to work with federated learning this month and your video was super nice to make me understand better this topic. I am going now to check your tutorial :) Thanks a lot!
I was just wondering about the difference between differential privacy and federated learning and this video showed up just in time to explain exactly that. What a gem! Thank you so much.
Nice explanation. Just wanted to point out that differential privacy can also be achieved by adding noise to a model or its gradients, rather than to the data directly
Thanks for taking the time to put together this well explained video. It’s great that you added a notebook for exploring more deeply what you explained in the video. Nice work!
Do you think it would possible for someone who's only programming background would be intro to computer science, in both python and java, to learn enough on their own about Federated Learning to make a career out of it? Or would you need a compsci degrees worth of knowledge? great explanation btw
Firstly I liked the concept explanation. I am currently working on a research project related to federated learning and had a few queries I would like to get resolved. I cannot ask them here due to the potential thief of the research idea. Is there any way I can get in contact with you?
Hi Jordan, thanks a lot! While running in your colab I got an error on importing syft: AttributeError: type object 'Tensor' has no attribute 'fft' Could you please check? Thanks
jialiang xu according to my understanding there are not in-built functions for DP in pysyft. They use numpy Laplace function to add noise to the original answer.
It's not focusing on something is dating someone by biracial issues on something when I did not say that anybody they fired me so how many years ago you been doing it
Home is the security invading the privacy of the whole racial gesture about it and it's not cold related issues I am not related to anybody on here and my account has been abated bothering my account mental disorder
A note on the Federated Learning example in the Colab tutorial (which is also pointed out on the OpenMinded tutorial) - this is meant to show how the learning process works when you're pulling from separate datasets, but this process actually doesn't ensure privacy! You can call model.get() to learn about how to predict well on Alice's data without having seen it, which can help you learn more about the dataset itself, even potentially replicating it perfectly. A way to avoid this is to average Bob and Alice's model updates before sending them to the global model as we talked about in the video! Thanks to u//raj111sam for pointing this out on the r/artificial subreddit.
Great video I’m a Technical Pm and been heavy in Data and Analytics. What are your thoughts on the MIT Business Analytics 6 weeks program? What do you recommend?
Hey Jordan :) I am a postdoc researcher based in Japan, but originally from Brazil. I have started to work with federated learning this month and your video was super nice to make me understand better this topic. I am going now to check your tutorial :) Thanks a lot!
Great job. Please do a video on Continual Learning + Differential Privacy.
I was just wondering about the difference between differential privacy and federated learning and this video showed up just in time to explain exactly that. What a gem! Thank you so much.
Nice explanation. Just wanted to point out that differential privacy can also be achieved by adding noise to a model or its gradients, rather than to the data directly
Seeing 0:50, I know this video definitely worths a thumbs up.
Would definately like to see more coding examples.
Awesome! I’ll try to keep making these for future AI 101 videos. The next one should be interesting ;)
Thanks for taking the time to put together this well explained video. It’s great that you added a notebook for exploring more deeply what you explained in the video. Nice work!
Hey Jordan, I'm new at federated learning, your video was really nice!
@JordanHarrod Thank you for this lovely video. Is there a video that explain the code you shared in Colab ?
Thanks! I’m doing a short presentation about these topics for my data science boot camp
This was very informative, Jordan. Thanks for the great explanation!
Great video
Please do more or an update on privacy protection
4:21 - Would be very interested in an Analysis of Whoop and your thoughts on it!
Dear Jordan, Thanks so much for this video and link. I was looking for this kind of information. Thanks a lot again.
awesome, here for the coding walkthrough
Short video but informative. Thanks for sharing.
Great video. So happy I subscribed. You always make something interesting and informative 🤘🏾🤘🏾
Thank you!
Good one to start with. Can you add a tutorial or reference for private network setup or remote worker setup using torch and pysyft.
3:07 - It's not just medical data either, with enough data points, you can de-anonymize anything. That's how Panopticlick works.
Definitely true! I'm planning a video on how this works in the next couple months.
hi, how to combine DP and FL together?
Would definetely like to see coding exampels
The coding session can really help giving a deeper insight. Do it more...
Will do!
THank you
Do you think it would possible for someone who's only programming background would be intro to computer science, in both python and java, to learn enough on their own about Federated Learning to make a career out of it? Or would you need a compsci degrees worth of knowledge? great explanation btw
I definitely think it's possible!
great ! thanks
It is showing an error that module 'syft' has no attribute 'TorchHook'. Please tell me how to resolve it...
I'm encountering the same error.
Great Video!!
Thank you!
Firstly I liked the concept explanation. I am currently working on a research project related to federated learning and had a few queries I would like to get resolved. I cannot ask them here due to the potential thief of the research idea. Is there any way I can get in contact with you?
Hi Jordan, thanks a lot! While running in your colab I got an error on importing syft: AttributeError: type object 'Tensor' has no attribute 'fft'
Could you please check?
Thanks
A specific version of syft would be working fine
it was awesome but if you were to explain the code it would be exciting though.
Can we perform differential privacy queries with pysyft?
do u have the answer?
jialiang xu according to my understanding there are not in-built functions for DP in pysyft. They use numpy Laplace function to add noise to the original answer.
@@factology124 ok~thanks~
I like your hair
It's not focusing on something is dating someone by biracial issues on something when I did not say that anybody they fired me so how many years ago you been doing it
she know ai i think am in love
Hey,
Can I have your email?
Home is the security invading the privacy of the whole racial gesture about it and it's not cold related issues I am not related to anybody on here and my account has been abated bothering my account mental disorder