Absolutely amazing video course. Especially after looking at other sources I notice how valuable this is. Every video achieves to combine the intuition and math in a concise was. I recommend the videos to anyone who wants to learn about ML.
23:20 perplexity - adjust sigma for each i so that we reach perplexity=30. may be small in dense group, but big in sparse group. 43:40 crowding problem
t-SNE is 1) non-linear 2) non-parametric (aka stochastic, non-deterministic) 3:28-4:20 8:46 MNIST 9:22 PCA's visual 17:1417:57 18:45 t-SNE's visual 31:29❗2 separate blue clusters cannot get together 32:41 the fix: increase "Early Exaggeration" temporarily to increase the attraction force and then decrease back
Great lesson. How can you use t-SNE not just for visualization but also for classification? Does t-SNE take into account that some variables are more related with the formation of the cluster and other just add noise? I mean, in some moedls you can calculate the p-value and the SHAP for each variable. Can you get this kind of information here?
Absolutely amazing video course. Especially after looking at other sources I notice how valuable this is. Every video achieves to combine the intuition and math in a concise was.
I recommend the videos to anyone who wants to learn about ML.
The best video on this topic I have found so far by a large margin. Excellent work!
Excellent presentation
Worth every second. You are a blessing to humanity.
23:20 perplexity - adjust sigma for each i so that we reach perplexity=30. may be small in dense group, but big in sparse group.
43:40 crowding problem
Cool explanation and visualizations!
what an amazing explanations.......................well done............BRAVO!
t-SNE is 1) non-linear 2) non-parametric (aka stochastic, non-deterministic) 3:28-4:20
8:46 MNIST
9:22 PCA's visual
17:14 17:57
18:45 t-SNE's visual
31:29❗2 separate blue clusters cannot get together
32:41 the fix: increase "Early Exaggeration" temporarily to increase the attraction force and then decrease back
Thank you for your awesome explanation and illustrations nive thank you very much
amazing lecture. Please post more videos.
Amazing course with great vizualisations ! thank you very much
Wonderful job. Really enjoy watching this.
So well explained! The best video resource I have seen on t-SNE so far!
Thank you for this course!
Incredibly explained. Congratulations!
It is an amazing course, worth the time to watch and learn from it.
Amazingly explained, It's such a great resource.
Fabulous video! This was really helpful, thank you!
Excellent talk with spot on visuals and explanations. Thanks!
Amazing Lecture, very well explained! Thank you for sharing!
Top quality lecture, thanks for sharing
Great explanation with both details and good examples
Awesome explanations. Thank you very much.
Thanks a lot for greay content
Beautiful explanations!
Excellent lecture, thanks
Great lesson.
How can you use t-SNE not just for visualization but also for classification?
Does t-SNE take into account that some variables are more related with the formation of the cluster and other just add noise?
I mean, in some moedls you can calculate the p-value and the SHAP for each variable. Can you get this kind of information here?
Bravo! Thank you very much.
Amazing! Super interesting and understandable!
how can one get good results with PCA init as don't we lose valuable non-linear information?
amazing content
Amazing!
amazing, thx.
Greetings from Spain
Very good lesson
This video is the bees knees
The dogs bollocks
Where can we find lecture notes?
Use the subtitles/closed captions?
Respect!
It's like your cup when u add the coffee powder into water