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
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?
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
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 talk with spot on visuals and explanations. Thanks!
Amazingly explained, It's such a great resource.
Incredibly explained. Congratulations!
Amazing Lecture, very well explained! Thank you for sharing!
It is an amazing course, worth the time to watch and learn from it.
what an amazing explanations.......................well done............BRAVO!
Wonderful job. Really enjoy watching this.
Amazing! Super interesting and understandable!
Great explanation with both details and good examples
Fabulous video! This was really helpful, thank you!
Beautiful explanations!
So well explained! The best video resource I have seen on t-SNE so far!
Top quality lecture, thanks for sharing
Amazing course with great vizualisations ! thank you very much
Awesome explanations. Thank you very much.
Worth every second. You are a blessing to humanity.
Thank you for this course!
Thank you for your awesome explanation and illustrations nive thank you very much
Bravo! Thank you very much.
Excellent lecture, thanks
amazing content
Thanks a lot for greay content
Amazing!
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
amazing lecture. Please post more videos.
Respect!
amazing, thx.
Greetings from Spain
Very good lesson
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?
This video is the bees knees
how can one get good results with PCA init as don't we lose valuable non-linear information?
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
It's like your cup when u add the coffee powder into water
Where can we find lecture notes?
Use the subtitles/closed captions?