The Viterbi Algorithm : Natural Language Processing

How to efficiently perform part of speech tagging!
Part of Speech Tagging Video : • Part of Speech Tagging...
Hidden Markov Model Video : • Hidden Markov Model : ...
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[@DistortedV12]

NLP students in the future are going to love this

[@utkarshgarg8783]

I am a NLP student and I am lovin' this :)

[@LeonPark]

lovin it

[@thepriestofvaranasi]

Lovin it bro, you're a visionary

[@xzl20212]

I do

[@bedoor109]

True

[@raghavarora3044]

This was honestly one of the few videos where someone has actually explained something so clearly and efficiently! Great job! Keep up the good work!

[@ritwikgoel]

Deadass

[@r2d2b3c4]

Mate, I just had a lecture on Viterbi in NLP context from uni and I was having nearly a breakdown due to all the smart formulas our teacher has gave us. It was not possible to understand it for me from the lecture. But you have shown it and explained it so clearly, I am amazed and shocked at the same time. You are a legend! Please carry on with the videos, you are saving and changing lives with this

[@muradal-ahmad4048]

Awesome video, very informative! Viterbi explanation starts at 07:28, if you're somehow familiar with HMMs basic concept.

[@sashankvemulapalli6238]

This literally has to be the best resource to understand Viterbi algorithm across the whole of the internet. Even the inventor themselves wouldn't have been able to explain it better!!! THANKS A TON

[@croncoder862]

Very well explained, I actually came from the Coursera NLP specialization since I had many doubts over there, but after watching this, everything is clear.

[@devindoinmonkmode]

Me tooo, this guy is damm crazy

[@yurimuniz7]

Same here. My expectations were high with that course given the quality of the deep learning specialization. But I'm kinda disappointed so far. I've been learning much more from materials like this over the internet.

[@kewtomrao]

I had the same doubt you had at around 13:30 , but you cleared it without causing any confusion!!! Awesome explanation!!! Hopefully your channel becomes more popular!! cheers and good day ahead!!

[@Mew__]

Exactly. I couldn't be convinced when I was told Viterbi isn't greedy, but it makes sense now. Essentially, there's a big difference between argmax of the next connection, and argmax of the cumulative previous connections.

[@unlimitedsky8506]

The prove of the dijkstra invariants is very similar to how you would prove the statement with the viterbi algorithm. In case you're interested in the exact prove!

[@libertylocsin4666]

NLP student here. Love this. Your my hero. :D

[@anirudhgangadhar6158]

One of the best explanations I have ever come across. I was struggling with POS tagging a bit but now its crystal clear. Thanks a lot :)

[@YuryGurevich]

This is the best explanation I have encountered. Thank yup very much.

[@farnaznouraei8351]

The best explanation I've seen on this topic. Thank you!

[@SajjadZangiabadi]

The teacher does an excellent job of explaining the Viterbi Algorithm and providing a clear example. It’s always great to see educators who are passionate about their subject and able to convey complex concepts in an understandable way.

[@brendanking6326]

Super helpful explanation on exactly when you can discontinue the candidate paths. I've seen a few explanations of that point and this one is definitely the clearest

[@tarunr130]

The best way, anything academic related, has ever been explained to me on KZbin. Amazing!! Thanks a lot.

[@hossainalif3909]

I'm not gonna say I can solve all the problems of veterbi algorithm from now on, but I can say I have a clear concept after watching this, thank you sir....

[@ritvikmath]

Of course!

[@naveen_malla]

Dude this is awesome. I came here because I did not uderstand the explanation of a Coursera course. No offense to them but you did a great job. Thank you.

[@ritvikmath]

Glad it was helpful!

[@sethcoast]

Amazing explanation thank you!

[@flyingsnowball9224]

This is THE BEST lesson on the Viterbi algorithm ever. THANK YOU!

[@noorulaminbhat]

One of the best videos on the subject, that I have ever watched. Great work and keep it up!

[@utkarshgarg8783]

This video can never have a dislike. Simply amazing Ritvik. Thanks!

[@NaifAlqahtani]

My guy.. you have a way with words. Ma Sha Allah. beautifully explained

[@ngocquangle5975]

thank you so much, it took me so much time to learn this

[@wonbulzhang2240]

teaching slowly, but it is very clear. Good job!

[@emid6811]

Thank you so much! I learned a lot. 👏

[@leonardliu1995]

Very good video! Cleared up my doubts about why we can't have branch pruning of the lower probability branch! Thanks a lot!

[@wenerjy]

Thank you so much, I had the same questions as you!!

[@ginkei]

Genuinely the best explanation there is, Enlightenment reached!

[@raamdemaas]

The explanation is amazing. Couldn't wrap my head around it earlier with the text book

[@thealiens386]

I have 11 hours to my algorithms exam, this video helped so much thank you!

[@AnhNguyen-df1nm]

God damn what a thorough explanation. Respect brother

[@simiouch5128]

Very clear and instructive explanation. You're a great teacher :) Thank you for these videos

[@smangla07]

Awesome video. Clearly explains a difficult to comprehend algorithm

[@ritvikmath]

Glad it was helpful!

[@MattRosinski]

Beautiful clear explanation! Thanks Ritvik!

[@rxs5556]

This video finally nailed it for me. Thanks!

[@proteus333]

This video was so good I loved it, thank you so much!

[@SaiGollapudi]

Awesome job! Simple explanation. Pls continue to make such videos.

[@ritvikmath]

Thanks a lot!

[@elaine19931120]

Thank you, it's much clearer than my professor

[@rajkumarvasan1]

Amazing explanation on Viterbi. Thank you so much for this. Could you please do a video on Baum Welch Algorithm?

[@kanikagupta6103]

bhaiya thank you so much ! had some much difficulty coz everyone explained easy half of it.. but you did amazing job !!!!

[@LiIRobJr]

I understood this the first time he explained it. Great video man

[@Ram-vu4lk]

Calmly explained to make this algorithm understandable in intuitive way. :)

[@prepotente_irreale]

Thanks for the amazing, structured and pretty damn good video and explanation :)

[@danieldrew2356]

thanks very intuitive and well planned video - was really easy to follow!

[@ritvikmath]

Glad it was helpful!

[@Abhishek-pb8kt]

Wonderful 🎉 very engaging and beautifully explained.

[@guppy13]

You made this very easy to understand, thank you

[@ritvikmath]

You're very welcome!

[@aryasharma9379]

Really well explained! You are a great teacher.

[@sarasterlie4799]

This channel is a lifesaver! Thank You!!!

[@lechx32]

This is a very clear explanation, thank you

[@supervince110]

Your explanation is brilliant

[@matthewmoore6116]

You my friend, are very good at teaching

[@jannisn.3600]

Insanely well explained, thank you very much!

[@MGtvMusic]

Amazing Video! Was Stuck at this part for so long

[@funskill-relaxationsounds7521]

This helped a lot bro! God bless you

[@godsarsehole]

absolute lifesaver

[@josy4767]

Really great - I was really able to follow along

[@sudhanshurai1146]

you earned a subscriber man. Very well explained.

[@DemianUsul]

This is incredible well explained. Thank you and congratulations 🎉

[@agnelomascarenhas8990]

Vitterbi algorithm was well explained. Hidden Markov Model was a bit difficult to follow because the contrast on whiteboard was low. I like the way you explain keeping formal clutter out of the way.

[@hhehe24]

very clear and direct, thanks

[@mycodeKK]

Thanks man you're thousand times better than my prof.

[@vipulmishra8682]

That was a great video! Your exlanation is very clear! Thanks a lot!

[@marouanebenbetka]

Clear Explanation, Thank you!

[@xraymao5405]

Huge thank you for this great content. It is truly gold

[@Xnshau]

Brilliantly explained 👍

[@selwia.771]

Excellent explanation. Thank you very much

[@meghajohn]

Very well explained. Clear and succinct!

[@茱莉-x2o]

very clearly explained. thank you very much

[@HadiAhmed7546]

Hey thanks for the video - its super helpful - just one question. When you branched off the start node you only considered the possible state as DT, but isnt there also a 0.2 prob that the first state is a NN?

[@richardfutrell9668]

The transition from start to NN is possible, but the emission probability for "the" given NN is zero so we can skip it.

[@boosterfly]

Just subscribed! This is awesome!

[@kanhabansal524]

best explanation over internet

[@ritvikmath]

Wow thanks!

[@darshansolanki5535]

Great content, excited to see more videos on parse trees and sentence correctness grammer

[@mananlalit]

Very nice explanation!

[@totoro_r1668]

Really like your video, it's super clear even for me, who come from a linguistic background! Thank you

[@אליהשלמה-ב8י]

excellent explanation

[@kiran5918]

So good, it makes me cry

[@ritvikmath]

Thanks!

[@coupmd]

You're a legend. Thank you so much!

[@gigabytechanz9646]

very clear and detailed explanation! Thanks

[@cicidu8577]

This is so clear! Thank you so much!

[@xy11021]

Great video, greetings from munich, lmu ! Thanks you

[@souravganguly5680]

Beautiful explanation

[@francisst-amour646]

very good presentation

[@trejohnson7677]

This algorithm is appealing to the sensibilities. You can feel the authors nature & propensities.

[@ArminBishop]

Finally, I understood it. thanks.

[@murkyPurple123]

Brilliant explanation!

[@jerilynliu8956]

Thank you for this amazing video! It is so informative and time-saving :D

[@KarmaKomet]

Great explanation!

[@ritvikmath]

Glad it was helpful!

[@calpal9871]

Great video. Thank you!

[@annatigranyan6417]

Excellent explanation. Thank you :)

[@FullStackAmigo]

Very good explanation! Thanks a lot.

[@yangwang9688]

Looking forward to coding viterbi algo from scratch!

[@ray...]

I love you, man.

[@일언-s2p]

Hey, thank you so much for sharing all of these helpful videos with us. I really appeciate it! I can see you explained about the decoding algorithm with HMM. Could you also explain about evaluation and learning algorithms?

[@ramankumar41]

Great effort !!!

[@mmmmiru]

love your shirt!

[@ritvikmath]

Thanks!

[@SignalFlux]

Great video, you are a great explainer. One note, are you sure that the reason why Viterbi is fast (O(L*P^2) rather than O(P^L)) is because you can discard paths (13:49)? It seems to me like the generic Viterbi formulation does not discard any paths (as it seems from the pseudo code on wikipedia), rather it's efficiency comes from the very nature of a dynamic program where the algo builds on previous work in a smart way (overlapping sub problems etc...). As you yourself say at the very end (19:57), you look at all nodes in the previous layer at each step. At each layer there are P nodes and at each node there are P options, which repeated L times means there are L*P^2 ops to do. So I guess it's not even necessary for Viterbi to prune paths to reach that good of a runtime.

[@liltarnation2641]

Absolute legend

[@jetlime08]

Amazing video ! Thanks for the great contribution :)

[@ramtinfarajollahi7250]

not used to commenting, but thank you, subscribed as well

[@encodecode1059]

Excellent video

[@ritvikmath]

Thanks!

[@Kishan31468]

0 dislikes in the video tell everything. Damn Amazing.