I have been learning about machine learning for about 2 weeks now. Mostly from reading articles and watching youtube videos. For the latter category, I have to say your videos and blogposts really are in a league of their own. Looking forward to watching the rest of this tutorial collection! Thank you!
These videos are amazing, everything from narrating the papers, the subtle animations and the extra clips of conferences for awareness! To contribute to the question of the video, I've been learning machine/deep learning for a bit over a year now, and I've come further than I would have anticipated. If only I had known about these videos before.
Thank you Ulm! Really appreciate that. Also, very happy to see your participation in the comments over the last few videos. Awesome! "I've come further than I would have anticipated." - Be proud of that. Means you're pushing the boundaries! 🚀
Didn't know earlier that Fashion-MNIST is in the same input format as MNIST dataset and can be (almost) directly plugged into your NNs. What a wonderful video!
Thank you for doing these lessons with exactly the right level of brevity and detail. I'm studying the deep learning field for a while, and your videos help me to fill in grey zones in my knowledge.
Very interesting! I've been studying ML full-time for about 6 months, and while I'd often heard about MNIST, I'd never heard of Fashion-MNIST. It was nice hearing the story behind it and looking at the actual paper: starting from a slightly different project rather than the usual MNIST makes me even more excited about writing my first nets with PyTorch (I've only been using Keras so far). Great video, keep it up!
@@deeplizard Yeah, and I'm finding it very useful: reviewing concepts more than once helps me truly understand them and implementing them in different ways makes me discover new things: for example, by learning PyTorch my understanding of Tensors and Classes has already improved a lot, and I love your approach of showing the actual library so I know what it's doing behind the scenes instead of using it as a black box ^^ I believe it's more natural to learn through repetition than just seeing something once and studying it a lot and trying to remember it: that's why I learn in waves, going over the same concepts multiple times through different approaches, and so far it's been working wonders ^^
@@deeplizard (I've also had a bug I've commented in the last video of your Reinforcement Learning series, a week ago or so. If you could check it out you'd do me a favor. I'll probably understand what I did wrong by furthering my understanding of the subject, but having an unfinished code is quite frustrating. Thanks again for the great videos!)
I have been interested in deep learning for the last 8-9 months and even used some pre-trained models in hackathons but had no idea wtf was really happening but now that I am actually learning this, it feels amazing!
Deeplizard, I am using your series for my science fair project and the production quality and effort really shine through. I truly appreciate your effort. Bravo. Also my project is concerning the applications of rnns for prediction of flood stages in bayous.
Hi Deeplizard, I have been interested in learning AI using pytorch as a bedrock since 3 years now, i bought 11 different courses on Udemy but to no avail, i still don't understand the terminologies, algorithms and data preprocessing but thankfully i stumbled on your course which is perfect for a beginner to expert for free.. It's can't just be better than this. Thank you DeeeeeeeeeeepLizaaaard... I love you guys.
Its been almost 6 months studying machine learning and deep learning.... I am working on light weight CNNs to implement driver drowsiness detection on raspberry pi in real time... previously worked on keras but there were a lot under the hood... so I have started studying pytorch last week and your channel is the best online free source available...
man man man, I'm amazed by your content! so excited for the rest of the tutorial. Answer to the question, I've been doing lectures on ML for a year now, mostly fundamental ML, did lot of tutorials online, Udemy, Coursera, edX, you name it. Yours though, yours is kicking ass. Thank you.
Have been learning deep learning for a month using Keras. Everywhere, they say that Keras is for quick prototyping, I was always wondering as to what they may be using for regular machine learning! Recently I across the Kaggle interview of Shubin Dai, where he mentioned that he uses PyTorch to compete in all computer vision competitions, I got curious and then I came across this series. Thanks for this wonderful series.
I have heard of the Fashion MNIST dataset before. I played with a Tensorflow example code that uses the Fashion MNIST to train a deep learning model for classification.
heard mnist dataset while working on nn porj in MATLAB ... doing NN ML DL on MATLAB for around 2~3 years and now interested in learning pytorch for my next project... btw thanks for such wonderful series
I have heard of Fashion MNIST dataset before but never bothered to look who created it, what did the M and NIST in MNIST meant and the purpose of the dataset as a means to benchmark their algorithms. I am learning a lot from these videos. Thanks deeplizard for making such great content and keep up the good work :)
answers to Q: I've been interested in ML/neural nets for awhile but have only recently started to actively learn about them - I'm in a 4th year NLP course right now and we have to build a part-of-speech tagger with CNNs and PyTorch-after binge-watching this entire playlist today I don't feel quite as intimidated by the thought of starting this project, and I'm on the edge of my seat for your next video!! like others have already said, these vids are incredible and I wish more "for beginner" videos on ML were ACTUALLY suitable for beginners like these are. thanks a ton!!
Hey Luce - Thank you for sharing your experience! All in a day's work! lol. So fast! I appreciate you taking the time to comment and letting me know. Good luck with your NLP course! I'm glad you found this series helpful. 🚀
I've been interested in deep learning from past 6months and there are a lot of tutorials out there that confuse so much but this series by visual animations makes it so clear I wish I came across this series long before ..thankyou. #request for tensor flow and keras
I have been doing ML for 2 month now, but I find rather easy even without a good programming background. So it probably boils down to understanding of concepts and math more than knowing programming.
I think the narrative about AI being "biased" is simply misguided. The biases (if they exist) are present in the training dataset the model "learns" from. The programmer didn't code the bias. There is no method in the forward pass or the backpropagation that creates bias. And the biases (if they exist) may simply reflect the world we live in. To illustrate my point, a deep NN trained to evaluate loan applicants for a bank will certainly be biased against poor people. The dataset will include the loan repayment history of many, many borrowers. If economically disadvantaged people have a loan repayment history that is worse than others, the dataset will reflect that and the deep NN will learn that relationship.
Check out the corresponding blog and other resources for this video at: deeplizard.com/learn/video/EqpzfvxBx30
Oh God, this series should be considered as pattern for each who want to create tutorial. Thanks for great explanation!
I have been learning about machine learning for about 2 weeks now. Mostly from reading articles and watching youtube videos. For the latter category, I have to say your videos and blogposts really are in a league of their own. Looking forward to watching the rest of this tutorial collection!
Thank you!
These videos are amazing, everything from narrating the papers, the subtle animations and the extra clips of conferences for awareness!
To contribute to the question of the video, I've been learning machine/deep learning for a bit over a year now, and I've come further than I would have anticipated. If only I had known about these videos before.
Thank you Ulm! Really appreciate that. Also, very happy to see your participation in the comments over the last few videos. Awesome!
"I've come further than I would have anticipated." - Be proud of that. Means you're pushing the boundaries! 🚀
Didn't know earlier that Fashion-MNIST is in the same input format as MNIST dataset and can be (almost) directly plugged into your NNs. What a wonderful video!
I have been Interested in machine lerning in the last ~2-3 years. Loving this series! Great job
Thank you for doing these lessons with exactly the right level of brevity and detail. I'm studying the deep learning field for a while, and your videos help me to fill in grey zones in my knowledge.
Very interesting! I've been studying ML full-time for about 6 months, and while I'd often heard about MNIST, I'd never heard of Fashion-MNIST. It was nice hearing the story behind it and looking at the actual paper: starting from a slightly different project rather than the usual MNIST makes me even more excited about writing my first nets with PyTorch (I've only been using Keras so far). Great video, keep it up!
Thank you for sharing some of your experience. Glad to hear you are learning multiple libraries 😊
@@deeplizard Yeah, and I'm finding it very useful: reviewing concepts more than once helps me truly understand them and implementing them in different ways makes me discover new things: for example, by learning PyTorch my understanding of Tensors and Classes has already improved a lot, and I love your approach of showing the actual library so I know what it's doing behind the scenes instead of using it as a black box ^^
I believe it's more natural to learn through repetition than just seeing something once and studying it a lot and trying to remember it: that's why I learn in waves, going over the same concepts multiple times through different approaches, and so far it's been working wonders ^^
@@deeplizard (I've also had a bug I've commented in the last video of your Reinforcement Learning series, a week ago or so. If you could check it out you'd do me a favor. I'll probably understand what I did wrong by furthering my understanding of the subject, but having an unfinished code is quite frustrating. Thanks again for the great videos!)
I have been interested in deep learning for the last 8-9 months and even used some pre-trained models in hackathons but had no idea wtf was really happening but now that I am actually learning this, it feels amazing!
I really appreciate the use of interview and conference media. Thank you for producing such thoughtful material.
You are welcome! Thank you for taking the time to let me know!
Deeplizard, I am using your series for my science fair project and the production quality and effort really shine through. I truly appreciate your effort. Bravo. Also my project is concerning the applications of rnns for prediction of flood stages in bayous.
Hi Deeplizard, I have been interested in learning AI using pytorch as a bedrock since 3 years now, i bought 11 different courses on Udemy but to no avail, i still don't understand the terminologies, algorithms and data preprocessing but thankfully i stumbled on your course which is perfect for a beginner to expert for free.. It's can't just be better than this. Thank you DeeeeeeeeeeepLizaaaard... I love you guys.
The series is awesome!!! we need more from you. Thank you so much.
Its been almost 6 months studying machine learning and deep learning.... I am working on light weight CNNs to implement driver drowsiness detection on raspberry pi in real time... previously worked on keras but there were a lot under the hood... so I have started studying pytorch last week and your channel is the best online free source available...
man man man, I'm amazed by your content! so excited for the rest of the tutorial. Answer to the question, I've been doing lectures on ML for a year now, mostly fundamental ML, did lot of tutorials online, Udemy, Coursera, edX, you name it. Yours though, yours is kicking ass. Thank you.
WOW! Your weren't kidding. lol! That means a lot. Thanks for sharing your experience. 🤖
Ive been interested in Neural Networks for 3 weeks. Have watched all you other vids in the series up to this point.
Hey Pranav - Nice! Thank you for your comments and sharing! 🚀
Have been learning deep learning for a month using Keras. Everywhere, they say that Keras is for quick prototyping, I was always wondering as to what they may be using for regular machine learning! Recently I across the Kaggle interview of Shubin Dai, where he mentioned that he uses PyTorch to compete in all computer vision competitions, I got curious and then I came across this series. Thanks for this wonderful series.
You are very welcome, and thank you for all of your comments! Really appreciate you taking the time to leave them.
I have heard of the Fashion MNIST dataset before. I played with a Tensorflow example code that uses the Fashion MNIST to train a deep learning model for classification.
Thanks a lot for these videos, helps learning this feel a lot easier than before!
heard mnist dataset while working on nn porj in MATLAB ... doing NN ML DL on MATLAB for around 2~3 years and now interested in learning pytorch for my next project... btw thanks for such wonderful series
I have heard of Fashion MNIST dataset before but never bothered to look who created it, what did the M and NIST in MNIST meant and the purpose of the dataset as a means to benchmark their algorithms. I am learning a lot from these videos. Thanks deeplizard for making such great content and keep up the good work :)
Hey Vinayak - Thank you for letting me know! Glad you are learning! 🚀
answers to Q: I've been interested in ML/neural nets for awhile but have only recently started to actively learn about them -
I'm in a 4th year NLP course right now and we have to build a part-of-speech tagger with CNNs and PyTorch-after binge-watching this entire playlist today I don't feel quite as intimidated by the thought of starting this project, and I'm on the edge of my seat for your next video!! like others have already said, these vids are incredible and I wish more "for beginner" videos on ML were ACTUALLY suitable for beginners like these are. thanks a ton!!
Hey Luce - Thank you for sharing your experience! All in a day's work! lol. So fast! I appreciate you taking the time to comment and letting me know. Good luck with your NLP course! I'm glad you found this series helpful. 🚀
Very insightful. Thanks.
love this series
DeepLizard for president
+1 from me
Amazing content, This is waaay better than all those paid courses...
i loved this tutorial much. because it explains every thing in Details.
I've been interested in deep learning from past 6months and there are a lot of tutorials out there that confuse so much but this series by visual animations makes it so clear I wish I came across this series long before ..thankyou.
#request for tensor flow and keras
Thank you, Rishabh! We do have a Keras series available below here :)
deeplizard.com/learn/playlist/PLZbbT5o_s2xrwRnXk_yCPtnqqo4_u2YGL
I am training, using and improving my neural network since I was born.
🤖
Твои видео просто золото)
I have been doing ML for 2 month now, but I find rather easy even without a good programming background. So it probably boils down to understanding of concepts and math more than knowing programming.
You are awesome ❣️ thank you very much for great lectures
hi sir im a beginner thanks for clearing all my doubts n i need the link to download the fashion mnist dataset
Comes to learn PyTorch.
Leaves as an expert on various datasets commonly used around the world.
Hey Ravi - You are really moving! I think you may be setting a record for binging this series! 🥇
Thank you for commenting along the way!
i really like those 'quoets in your videos,
Hey Sina - Glad you like those! Thanks for your feedback!
and absolutely your teaching method, waiting for more pytorch videos.
Great video
🙏
Sorry to say that but, I have no idea about the Fashion-MNIST dataset before. I am in this Neural Network field for 1 year.
You R awesome!!!
tnx
3 years
I think the narrative about AI being "biased" is simply misguided. The biases (if they exist) are present in the training dataset the model "learns" from. The programmer didn't code the bias. There is no method in the forward pass or the backpropagation that creates bias. And the biases (if they exist) may simply reflect the world we live in. To illustrate my point, a deep NN trained to evaluate loan applicants for a bank will certainly be biased against poor people. The dataset will include the loan repayment history of many, many borrowers. If economically disadvantaged people have a loan repayment history that is worse than others, the dataset will reflect that and the deep NN will learn that relationship.
Mandy's english accent? XD
get rid of the berserk TV clips
Andrej should not attempt to talk
2 years