A friendly introduction to linear algebra for ML (ML Tech Talks)

[@EvertRoz]

Not only a friendly introduction but also a friendly person to listen to. Very well done. Thanks.

[@abiiranathan]

The best talk I have ever seen. I smiled when she explained issues I have always struggled with and I left feeling like an expert...Her warm smile and sweet voice is mind blowingly calming

[@master_braure]

same

[@hyunbyungpark8165]

I've studied linear algebra and all kind of math for a long time. And this presentation is one of the most beautiful things I've seen. I'm touched. I can't even think about a better way to explain the same thing better than this.. Why i saw this so late? I feel I lost my time too much.

[@ib_parametres724]

Years of learning linear algebra and this roughly 40 min video just put everything into perspective, wow. I had picked up Steve Brunton's Data-Driven Science and Engineering book a few years ago to learn data science and just a few pages in, I run into SVD and all these terminologies that he provided codes for how to compute, but I was just missing the whole point. Watching this video, I think most of those concepts make sense now. Thanks, Tai-Danae Bradley and TensorFlow, for this simple and clear explanation.

[@powerranger3223]

I am such a visual learner and appreciate all the diagrams and color coding it made everything so much more clearer!!!

[@sanketss84]

that was such an amazing video. much thanks for simplifying these concepts in maths and how they actually relate to ML. this is exactly what I wanted to understand.

[@trackhero2714]

I would looove to learn more maths from Tai-Danae Bradley. This just popped up in my feed and I love how she explains stuff. Great teaching right here.

[@vandalphilosopher1971]

You can try with the last videos of PBS Infinite Series, she hosted many videos towards the the end of the active period of the channel.

[@CamiloAM20]

She has a blog! Math3ma

[@Ash-bc8vw]

check out her math blog called mathema

[@informativecontent4778]

@@CamiloAM20 share link plz

[@nabeelhasan6593]

This is a beautiful example of how mathematics should be explained

[@zrmsraggot]

Go check 3b1b series they are amazing

[@Artaxerxes.]

@@zrmsraggot She did mention 3b1b at the eigenvectors and dimensionality reduction part. Just noticed they even linked 3b1bs vids which is nice

[@aaroncowan7283]

@@zrmsraggot She was recently featured on his podcast as well!

[@MichaelMantion]

Really? I thought it was rambling, repetitive yet lacking.

[@zoemoorton9570]

The most accurate statement on the internet.

[@JBoy340a]

One of the best talks I have ever seen on Math and ML.

[@MichaelMantion]

That is sad... very very sad.

[@ShaunYCheng]

Any other recommendations?

[@waatchit]

Wow. What a lecture. Tons of info in. Such a short span of time with great clarity. Need more of such short and sweet lectures. Big thanks to the lecturer.

[@ulugbeksalaev3399]

I don't believe that she is only a mathematician. Very nice explanation from a mathematician I have ever seen.

[@ToreyLittlefield]

Thank you for the video. As someone learning ML and with a little rusty linear algebra understanding this was a perfect intro. 👍

[@Galmion]

I would love it if you were to upload more long-form talks like this one. amazing content!

[@amosmunezero9958]

Coming from Computer science background, lady you are genius! man I have done College Linear Algebra and ML courses, but your explaination really made me appreciate these concepts much more - So thank you and God bless you!

[@kailashbtw9103]

THIS is incredible, thank you so much Tai-Danae Bradley! Women in STEM rock! I am a girl working on her CS undergrad with an interest in machine learning and data science. I Had linear algebra already, and am taking regression models this semester. It is so incredible to me how these two subject I love intertwine to much.

[@chaochaisit]

Excellent presentation and voice! Math should always start with intuition and not generalized formula. Love this!

[@supersql8406]

Finally! An advanced topics such as Linear Algebra for ML!!

[@HitAndMissLab]

@Ms Bradley: Amazing! These intuitive overviews are so rare, but yours is just short of brilliant. Thank you very much.

[@eggressive_]

This presentator really good at elaborate! She really has a good intonation and voice!

[@gnsmrkyy7343]

Love the way you put cartoons and examples. Need more courses like this!

[@bac9982]

My only complaint is that this isn’t in the top rated videos on KZbin! This was such a well thought out lecture that covered things at a high level with just enough of a dip into the deep end to keep you wanting more. I realize not everyone needs this kind of information, but for those of us that are just getting started (the ones listening to people seemingly speak in a foreign language about math), this video is amazing! If you’re at all confused about all the data science related linear algebra that all the people around you are talking about, this will at least get you over the hump and moving in the right direction. Thank you for taking the time to make this and thank you so much for what you do to make the world a better place for us all!

[@GaryFerrao]

Oh. Where have i seen Tai-Danae? So many years ago at PBS Infinite Series!~ So glad to see her again 😄

[@paedrufernando2351]

I cant thank you enough for this detour...this came at the right moment when I wanted a context

[@bluestar2253]

Bravo! One of the best intro to Linear Algebra videos I've come across on YT!

[@narongsakkerdpol1211]

I subscribed just after a few minutes of listening. I’m a dad and my son will be studying computer engineering this fall. You made linear algebra fun again. Please keep more of math and related topics coming soon. Looking forward to more math.

[@IIAyogu]

Extremely illuminating. This is a great example of how to motivate learners. Please keep the videos coming.

[@therightangle6033]

Really well presented. Direct, relaxed and educational.... highly recommended

[@pamelamunkupa95]

I wasn't gonna watch this but your pulling force is outta this world. Thank you for this great explanation.

[@meniscusmedical2471]

Mindblowingly good, when you go through life and math teachers don't know how to teach this and you find this one math teacher who after years makes it go Aah so that's what you mean? That's what this amazing lady's lecture will do for 170,000+ viewers watching this. It's a like from me.

[@balaramkantipudi3728]

She did a fantastic job in explaining linear algebra behind ml

[@75hilmar]

The intro was very strong with many basic ideas that are really necessary for understanding these topics but I lost track somewhere around the middle. I suppose you could have called it a day after the first half and turn the second half into three to four equally interesting and informative sequels. Other than that you really went deep on picking new students up at the beginning and it has helped me a great deal with refreshing this important topic's basics.

[@daniel_caron]

Definitely one of the most insightful LA/ML talks on KZbin. Thanks!

[@harold.one.feather]

Use Google, 3Blue1Brown is much better

[@DataMaking]

Wow, oh my god, simply superb. I am commenting this message before completely watching this video. You explained very nicely all the concepts here. Big thank you for sharing this knowledge. Appreciate it Madam.

[@tanphan3970]

I spent much time to understanding these knowledges in the past. Your presentation in this video help me to good view for algebra in ML. Thank so much, I hope TensorFlow channel will post more same contents (comprehensive view in a topic)

[@millerdane]

I don't know how this came up in my feed but I am so glad. thanks youtube

[@edu-physics374]

Thank you, it is an interesting topic. How you explained also in a simple way of understanding. We are waiting to listen to another episode of this type of stuff.

[@ricardolourencosilva1741]

One of the best tutorials, I've seen. Congrats!

[@abderrahimbelissaoui2739]

I had a good linear algebra background before but now many things are clearer than before. Thanks for creating this content, looking forward to watching more similar videos on this channel!

[@dipmadk.b5774]

Yes Mam please do more content like this.. i feel that in my journey of Learning need a teacher or Mentor like you❤️(Respect)

[@santanukghatak3823]

Thank you for presenting the basic concepts in a very lucid way!!

[@adage3256]

Reminds me again that masters in a subject can explain the concept simply while not loosing the essence of it. Well done Tai-Danae Bradley!

[@modisaramoleko7220]

Hey there. Love your work at Black In AI. Beautiful to see different faces for once in a field of science and technology. Kudos

[@AbhisarMohapatra]

Man , this video is like an supercharged energy pill. So so good ✌️

[@mohamedfarah5306]

Appreciate the clear explanation of some concepts that I struggled with (SVD). I hope you can do more videos of ML.

[@salehmir9205]

Please do more content like this!

[@t2udu]

I don't consider myself bright, and I have only a passing interest in ML. But I was completely able to follow everything said here (granted it wasn't technical), and I suspect it's because of the skills of the content creator. Really good watch!

[@lioncaptive]

An excellent intro to Linear Algebra and its usefulness in ML that's further propelled by your clear communication skills.

[@filipesan]

Wonderful introduction to the topic. It made me understand so much better the connection between algebra and ML. It also made me understand much better what algebra is, as algebra was always explained to me in a very abstract way. Thank you for the video.

[@ogbeideaghahowa9004]

Wow! This must have taken a lot of time and effort to create. Thank you so much! You explain mathematics fantastically well.

[@imdadood5705]

This should be mandated upon all the people who are getting started with Machine Learning.

[@adamlasry1691]

What a great teacher! Thank you so much, Miss.

[@ulker17]

Just wow! most relaxing and beautifully explained math/ML lecture I have listened to!

[@priyavenkatesan1804]

Amazing explanation of complex topics in an easy to understand manner! Appreciate Math so much more now

[@jakejesus8904]

Fantastic explanation!. with this video my Machine Learning path becomes clearer.

[@zhuoyuelyu]

Great video! Thank you for creating this! 👏

[@sugiv]

Beautiful voice, pace, flow and content. Thanks. Great session. Thanks

[@harold.one.feather]

Linear algebra is a branch of mathematics that deals with vectors and matrices. Vector geometry is the study of geometric objects using vectors. Together, these two branches of mathematics can be used to interpret the dynamics of multidimensional space. One way to do this is to use linear algebra to represent the state of a system as a vector. The state of a system can be anything that can be described by a set of numbers. For example, the state of a particle in space can be described by its position and velocity. The state of a financial market can be described by the prices of stocks and bonds. Once the state of a system is represented as a vector, we can use linear algebra to study how the system changes over time. For example, we can use linear algebra to model the motion of a particle, the evolution of a financial market, or the spread of disease. In vector geometry, we can use vectors to represent forces, velocities, and accelerations. We can also use vectors to represent geometric objects such as lines, planes, and spheres. By combining linear algebra and vector geometry, we can develop a powerful mathematical framework for interpreting the dynamics of multidimensional space. This framework can be used to study a wide variety of systems, from the motion of particles to the evolution of financial markets. Here are some examples of how linear algebra and vector geometry can be used to interpret the dynamics of multidimensional space: * In physics, linear algebra is used to model the motion of particles, waves, and fields. * In chemistry, linear algebra is used to study the structure of molecules and the interactions between molecules. * In biology, linear algebra is used to study the structure of DNA and the dynamics of protein folding. * In finance, linear algebra is used to model the price movements of stocks, bonds, and other financial assets. * In computer science, linear algebra is used to develop algorithms for image processing, machine learning, and data mining. The applications of linear algebra and vector geometry to the interpretation of the dynamics of multidimensional space are vast and varied. These two branches of mathematics provide a powerful tool for understanding the behavior of complex systems.

[@TylerMatthewHarris]

Heyy! Tai-Denae from Infinite Series

[@exponode]

I'm doing my specialization in Datascience and this is very helpful for me Thanks For The Guide, SVD is awesome, Love this !

[@van-haunguyen4590]

concise and easy to understand. A brilliant work! Thank you.

[@zoemoorton9570]

I really really needed this, thank you so much! The way you explain everything is so clear and down to earth.

[@ighsight]

Bravo. It takes deep understanding to explain complex topics with this kind of simplicity and elegance. Google should consider paying Dr. Bradley's fee to do a full course playlist. Until then academia's gain is our loss.

[@alexb3617]

idk maybe i am delusional but i dont think any one of us can do any vector transformation or whatever is explained here after watching this video. so dont really see value in these kind of making excuses while not explaining stuff fully

[@oumski7529]

تحياتي الخالصة من الجزائر thank you very mutch

[@henrytzuo8517]

Thank you for the clear illustration!😊😊😊

People want a 4.0 version of this but with LLMs. 🙏🏻

[@Mohamed-um4rg]

Can be best presentation I have seen since long time . 👌👏

[@arturorenteria4943]

Thank you very much, a simple and very useful presentation!

[@aiwithaz]

Amazing!! Really found going straight to the application very useful!

[@bornkool]

WoW, ThankYou very much, This is great please explain ways we can use this math in practical ways. You Rock!!!!!!!!

[@JFaleiroJR]

Great video. Mathematics explained the way it should be. Will make sure to send this video to beginners in ML wanting to get to the basics of linear transformations. If I could make one suggestion, would be to drill a bit deeper in math, not much, just high school level. It would help students in connecting the subject to why they are seeing in the classroom. Good job.

[@cybervigilante]

Very good. I'd like to see something on Graph Theory. I'm learning linear algebra mainly as a way of looking into graph theory.

[@Salman-cx8qk]

Seriously underrated channel 👍

[@natal8261]

inspiring and, although I don't really deal with mathematics, I can see how brilliant this is!

[@NoNTr1v1aL]

Absolutely amazing video!

[@Wurfenkopf]

Hi, I'm a mathematician and all the explanation on the vector embeddings was great! However, since at 27:49 it is mentioned that the big matrix is approximated as U*V^T, I have to guess that the tick is represented by a 1 and the lack of a tick by a... -1? Because later in the explanation I see approximations of these two values, while I expected a 1 and a 0 according to the binary notation.

[@sk3ffingtonai]

Thank you for sharing this important topic in such an effective manner.

[@tedsheridan8725]

Great lecture! Really easy to follow. Even being familiar with Lin Alg, this gave me some cool insights on Data Science.

[@uty6595]

thanks for the clear and simple explanation, maybe there is machine learning hope for me afterall :)

[@SAAARC]

Excellently done! Loved the video. And I actually understood everything!

[@sammetsa]

Fantastic! Just what I’ve been looking for 😀

[@kenwee6527]

Thank you so much for this video! You are an amazing communicator and have such a great intuitive feel for the subject! Thank you for helping me understand!

[@SiphoNgwenya]

This was fun! Excellent talk!

[@manajitdas7619]

Thanks, it simple, nice and crisp...thanks a lot

[@nblaise21]

The best explanation I've seen, thank you so much!

[@gustavojuantorena]

Great video. I hope you do more like this in the future.

[@DerekWoolverton]

I'm not sure if you've ever watched the Triplets of Belleville, but I wouldn't exactly call it a kids movie. Would have loved to see the PCA approach applied to the movies matrix just to see what the eigenvalues were and how much was captured by those two first components.

[@yushpi]

Hi, May I know what playlist this is part of?

[@informativecontent4778]

Such a great mathematician

[@dedemenezes8452]

Well done! Amazing introduction video.

[@johnnovotny4286]

Excellent lecture. Pure magic.

[@ravishasharma7]

Lovely flow of explanation!

[@pritish3484]

Thank you. Simple, beautiful.

[@datouch]

Thanks for the video. Such great and simple explanations.

[@ManuelBasiri]

What an amazing presentation. Thank you 😊

[@ten2the6]

Well done and much appreciated!

[@lemurpotatoes7988]

Now that you mention it, I feel like there are probably statisticians who would yell at us for treating Likert scale rankings as vectors.

[@sdagupat1]

Very well done !! This is how you teach math.

[@masudcseku]

Great introduction in linear algebra ;)

[@haneulkim4902]

Amazing explanation! Thanks a lot Tai-Danae :)

[@faraazali9589]

Thank you for this video. You are such a great teacher.