Great video! I appreciate your guidance that Deep Learning is not easy in Java on slide 38 at 27:00. We have found that using a Python library, a Jupyter Notebook, and a GPU is the best way to create embeddings.
Hi all! I started studying Machine Learning in August, and just finished the introductory course. I remember we learned about Ridge Regression and The Lasso as two methods to shrink the amount of features, hence making it lower dimensional. Does that mean, per definition of Embedding, that Lasso and Ridge regression are embedding methods?
why does her voice sound like broken tape recorder or a radio that has bad antena... :D but nevertheless a very helpful talk on this topic , possibly amongst the best on youtube ! Thanks
This is the best definition of embedding for me.
The BLUF explanation alone was worth it.
you're awesome, this helped me quite a bit with my thesis.
Great video! I appreciate your guidance that Deep Learning is not easy in Java on slide 38 at 27:00. We have found that using a Python library, a Jupyter Notebook, and a GPU is the best way to create embeddings.
loved it! solved my problem with embedding...thanks!
Great video and explanation. it's so helpful to understand what is embedding...Thanks!
happy you enjoyed! Merci!
wonderful explanation. thanks a lot!
Love this , thank Alicia
Thank you Alicia that was helpful
Awesome explanation, thanks girl!
very informative and crisp :)
Awesome video. Thank you
amazing video thanks for sharing
Hi all! I started studying Machine Learning in August, and just finished the introductory course. I remember we learned about Ridge Regression and The Lasso as two methods to shrink the amount of features, hence making it lower dimensional. Does that mean, per definition of Embedding, that Lasso and Ridge regression are embedding methods?
great work
Hi, great video, is the presentation uploaded somewhere accesible?
Hey Nice work there!
P.S: Can you make a video on Graphsage?
Can we get embeddings for a node while training in supervised mode?
Well explained..
Nice video. On skipgram, I thought it predicts all words in the context window not just the next word though
You are correct.
How are you doing the graph path embeddings? - a link to a paper would be great
That was great...
Thanks
Its good!!!
tnx it was great
can you make video on sub2vec?
thx, very nice content. Would you share your slides please?
Million dollar question is: is there a pregel implementaiton.
Let's use pictograms as a word embedding (just for fun).
you should not put those animated gifs into your presentation :/ they really distract
why does her voice sound like broken tape recorder or a radio that has bad antena... :D
but nevertheless a very helpful talk on this topic , possibly amongst the best on youtube !
Thanks
I guess thats because of the mic
why u talking quickly !
i liked ur presentation but please dont run and eat words :) 😊